Biomedical Imaging

Exploring Scalable Medical Image Encoders Beyond Text Supervision

Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Matthew P Lungren, Noel Codella, Stephanie Hyland, Javier Alvarez-Valle, Ozan Oktay

Nature Machine Intelligence | January 2025, Vol 7: pp. 119-130

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MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models

Harshita Sharma, Valentina Salvatelli, Shaury Srivastav, Kenza Bouzid, Shruthi Bannur, Daniel Coelho de Castro, Maximilian Ilse, Sam Bond-Taylor, Mercy Ranjit, Fabian Falck, Fernando Pérez-García, Anton Schwaighofer, Hannah Richardson (nee Murfet), Maria Teodora Wetscherek, Stephanie Hyland, Javier Alvarez-Valle

Machine Learning for Health Symposium 2024 | December 2024

Publication Preprint Projet

OSAIRIS: Lessons Learned from the Hospital-Based Implementation and Evaluation of an Open-Source Deep-Learning Model for Radiotherapy Image Segmentation

Alexandra Constantinou, Andrew Hoole, David C. Wong, G. S. Sagoo, Javier Alvarez-Valle, Kenji Takeda, Tom Griffiths, Amy Edwards, Andrew Robinson, Liam Stubbington, Niall Bolger, Yvonne Rimmer, Thiraviyam Elumalai, K. T. Jayaprakash, Richard Benson, Ian Gleeson, Rebecca Sen, Louisa Stockton, Tian Wang, Stephanie Brown, E. Gatfield, C. Sanghera, Alexandros Mourounas, Barry Evans, Anita Anthony, Renteng Hou, Marian Toomey, K. Wildschut, Aviva Grisby, Gill Barnett, Rose McMullen, Raj Jena

Clinical Oncology | October 2024

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MAIRA-2: Grounded Radiology Report Generation

Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Anton Schwaighofer, Sam Bond-Taylor, Maximilian Ilse, Fernando Pérez-García, Valentina Salvatelli, Harshita Sharma, Felix Meissen, Mercy Ranjit, Shaury Srivastav, Julia Gong, Fabian Falck, Ozan Oktay, Anja Thieme, Matthew P Lungren, Maria Teodora Wetscherek, Javier Alvarez-Valle, Stephanie Hyland

MSR-TR-2024-18 | June 2024

Publié par Microsoft

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Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme

CHI 2024 | May 2024

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Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology

Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob

2405.05299 | May 2024

Publié par arXiv

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Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology

Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle

Nature Communications | March 2024, Vol 15

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RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing

Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse

ECCV 2024 | December 2023

Publication DOI Preprint Projet

MAIRA-1: A specialised large multimodal model for radiology report generation

Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Mercy Ranjit, Anton Schwaighofer, Fernando Pérez-García, Valentina Salvatelli, Shaury Srivastav, Anja Thieme, Noel Codella, Matthew P Lungren, Maria Teodora Wetscherek, Ozan Oktay, Javier Alvarez-Valle

MSR-TR-2023-47 | November 2023

Publié par Microsoft

Publication Projet

Exploring the Boundaries of GPT-4 in Radiology

Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle

EMNLP 2023 | October 2023

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Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay

The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023

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Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward

Anja Thieme, Aditya Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger

CHI 2023 | April 2023

Publication Projet

Using Thematic Analysis in Healthcare HCI at CHI: A Scoping Review

Robert Bowman, Camille Nadal, Kellie Morrissey, Anja Thieme, Gavin Doherty

CHI 2023 | April 2023

Publication

Deep Learning Models for COVID-19 Chest X-ray Classification: Preventing Shortcut Learning Using Feature Disentanglement

Caleb Robinson, Anusua Trivedi, Marian Blazes, Anthony Ortiz, Jocelyn Desbiens, Sunil Gupta, Rahul Dodhia, Pavan K Bhatraju, W Conrad Liles, Aaron Lee, Jayashree Kalpathy-Cramer, Juan M. Lavista Ferres

PLOS | October 2022

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Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay

The European Conference on Computer Vision (ECCV) | October 2022

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Active label cleaning for improved dataset quality under resource constraints

Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay

Nature Communications | March 2022, Vol 13(1161): pp. 1-11

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Effective Deep Learning Approaches for Predicting COVID-19 Outcomes from Chest Computed Tomography Volumes

Anusua Trivedi, Anthony Ortiz, Caleb Robinson, Jocelyn Desbiens, Marian Blazes, Sunil Gupta, Rahul Dodhia, Pavan Bhatraju, W Conrad Liles, Aaron Lee, Juan M. Lavista Ferres

Nature Scientific Reports | February 2022

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Machine Learning for Auto-Segmentation in Radiotherapy Planning

K Harrison, H Pullen, C Welsh, Ozan Oktay, Javier Alvarez-Valle, R Jena

The Royal College of Radiologists – Clinical Oncology | January 2022, Vol 34(2): pp. 74-88

Publication Projet Projet

Sociodemographic and clinical features predictive of SARS-CoV-2 test positivity across healthcare visit-types

Jimmy Phuong, Stephanie Hyland, Stephen J. Mooney, Dustin R. Long, Kenji Takeda, Monica S. Vavilala, Kenton O’Hara

PLOS ONE | October 2021

Publication Projet

fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data

Ruiyang Zhao, Burhaneddin Yaman, Yuxin Zhang, Russell Stewart, Austin Dixon, Florian Knoll, Zhengnan Huang, Yvonne W. Lui, Michael Hansen, Matthew P. Lungren

arXiv: Computer Vision and Pattern Recognition | September 2021, Vol arXiv:2109.03812

Publication Github Projet

Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs

Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro

ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021

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Addressing the Exorbitant Cost of Labeling Medical Images with Active Learning

Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

International Conference on Machine Learning in Medical Imaging and Analysis | June 2021

Best Presentation Award

Publication Projet

Automated Deep Segmentation of Healthy Organs in PSMA PET/CT Images

Ivan Klyuzhin, Guillaume Chausse, Ingrid Bloise, Juan M. Lavista Ferres, Carlos Uribe, Arman Rahmim

Journal of Nuclear Medicine | May 2021

Publication Projet

Secure Medical Image Analysis with CrypTFlow

Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare

NeurIPS PPML Workshop | December 2020

Publication Projet Projet

Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers

Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori

JAMA | November 2020

Publication Vidéo Github Projet

Binary Mode Multinomial Deep Learning Model for more efficient Automated Diabetic Retinopathy Detection

Anusua Trivedi, J. Desbiens, Ron Gross, S. Gupta, Juan M. Lavista Ferres, Rahul Dodhia

NeurIPS 2019 | December 2019

PDF Projet

Unsupervised Learning for Cell-level Visual Representation in Histopathology Images with Generative Adversarial Networks

Bo Hu, Ye Tang, Eric Chang, Yubo Fan, Maode Lai, Yan Xu

IEEE Journal of Biomedical and Health Informatics | May 2019

Publication Projet

Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge

Mitko Veta, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A. Shah, Dayong Wang, Mikael Rousson, Martin Hedlund, David Tellez, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Viana, Vassili Kovalev, Vitali Liauchuk, Hady Ahmady Phoulady, Talha Qaiser, Simon Graham, Nasir Rajpoot, Erik Sjöblom, Jesper Molin, Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Zhipeng Jia, Eric Chang, Yan Xu, Andrew H. Beck, Paul J. van Diest, Josien P. W. Pluim

Medical Image Analysis | March 2019

Publication Projet

3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context

Pawel Mlynarski, Herve' Delingette, Antonio Criminisi, Nicholas Ayache

Computerized Medical Imaging and Graphics | February 2019

Publication Projet

Unsupervised 3D End-to-End Medical Image Registration with Volume Tweening Network

Tingfung Lau, Ji Luo, Shengyu Zhao, Eric Chang, Yan Xu

February 2019

Publication Projet

Deep Learning with Mixed Supervision for Brain Tumor Segmentation

Pawel Mlynarski, Herve' Delingette, Antonio Criminisi, Nicholas Ayache

December 2018

Publication Projet

Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features

M. W. Macomber, M. H. Phillips, Ivan Tarapov, R. Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, M. J. Nyflot

Physics in Medicine and Biology | November 2018, Vol 63(23): pp. 235002-235002

DOI PDF Publication

Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features

Meghan W Macomber, Mark Phillips, Ivan Tarapov, Rajesh Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, Matthew J Nyflot

Physics in Medicine & Biology | November 2018, Vol 63(23)

Publication Projet

Autofocus Layer for Semantic Segmentation

Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya Nori

International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI) | September 2018

DOI Publication Projet

Semi-Supervised Learning via Compact Latent Space Clustering

Konstantinos Kamnitsas, Daniel C. Castro, Loic Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya Nori

International Conference on Machine Learning (ICML) | June 2018

Publication Publication Projet

MRI Image-to-Image Translation for Cross-Modality Image Registration and Segmentation

Qianye Yang, Nannan Li, Zixu Zhao, Xingyu Fan, Eric Chang, Yan Xu

January 2018

Publication Projet

Unsupervised End-to-end Learning for Deformable Medical Image Registration

Siyuan Shan, Wen Yan, Xiaoqing Guo, Eric Chang, Yubo Fan, Yan Xu

January 2018

Publication Projet

Gland instance segmentation using deep multichannel neural networks

Yan Xu, Yang Li, Yipei Wang, Mingyuan Liu, Yubo Fan, Maode Lai, Eric Chang

IEEE Transactions on Biomedical Engineering | December 2017

Publication Projet

Constrained Deep Weak Supervision for Histopathology Image Segmentation

Zhipeng Jia, Xingyi Huang, Eric Chang, Yan Xu

IEEE Transactions on Medical Imaging | November 2017

Publication Projet

Parallel multiple instance learning for extremely large histopathology image analysis

Yan Xu, Yeshu Li, Zhengyang Shen, Ziwei Wu, Teng Gao, Yubo Fan, Maode Lai, Eric Chang

BMC bioinformatics | August 2017

Publication Projet

Unsupervised domain adaptation in brain lesion segmentation with adversarial networks

Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia F.J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker

Information Processing in Medical Imaging (IPMI) | June 2017

Publication Projet

Spectral Kernels for Probabilistic Analysis and Clustering of Shapes

Loic Le Folgoc, Aditya Nori, Antonio Criminisi

Information Processing in Medical Imaging (IPMI) | June 2017

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Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features

Yan Xu, Zhipeng Jia, Liang-Bo Wang, Yuqing Ai, Fang Zhang, Maode Lai, Eric Chang

Bmc Bioinformatics | May 2017

Publication Projet

Image Quality Transfer and Applications in Diffusion MRI

Daniel C. Alexander, Darko Zikic, Aurobrata Gosh, Ryutaro Tanno, Viktor Wottschel, Jiaying Zhang, Enrico Kaden, Tim B. Dirby, Stamatios N. Sotiropoulos, Hui Zhang, Antonio Criminisi

Neuroimage | March 2017

Publication Projet

Sparse Bayesian registration of medical images for self-tuning of parameters and spatially adaptive parametrization of displacements.

Loic Le Folgoc, Hervé Delingette, Antonio Criminisi, Nicholas Ayache

Medical Image Analysis | January 2017, Vol 36: pp. 79-97

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Quantifying Registration Uncertainty with Sparse Bayesian Modeling

Loic Le Folgoc, Hervé Delingette, Antonio Criminisi, Nicholas Ayache

IEEE Transactions on Medical Imaging | December 2016

Publication Projet

DeepMedic for Brain Tumor Segmentation

Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker

MICCAI Brain Lesion Workshop | October 2016

DOI PDF Publication Projet

Lifted Auto-Context Forests for Brain Tumour Segmentation

Loic Le Folgoc, Aditya Nori, Siddharth Ancha, Antonio Criminisi

MICCAI Brain Lesion Workshop | October 2016

DOI PDF Publication Projet

Generalisability of Image Quality Transfer: Can we approximate in-vivo human brains from dead monkey brains?

Aurobrata Ghosh, V. Wottschel, Enrico Kaden, H. Zhang, Stamatios N. Sotiropoulos, D. Zikic, T. B. Dyrby, Antonio Criminisi, Daniel C. Alexander

April 2016

Publication Projet Projet

Decision Forests, Convolutional Networks and the Models in-Between

Yani Ioannou, Duncan Robertson, D. Zikic, Peter Kontschieder, Jamie Shotton, Matthew Brown, Antonio Criminisi

March 2016

DOI Publication Projet Projet

3D-SIFT-Flow for atlas-based CT liver image segmentation

Yan Xu, Chenchao Xu, Xiao Kuang, Hongkai Wang, Eric Chang, Weimin Huang, Yubo Fan

January 2016

Publication Projet

Assessing Multiple Sclerosis with Kinect: Designing Computer Vision Systems for Real-World Use

Cecily Morrison, Kit Huckvale, Bob Corish, Jonas Dorn, Peter Kontschieder, Kenton O'Hara, ASSESS MS Team, Antonio Criminisi, Abigail Sellen

Human-Computer Interaction | January 2016

Publication Publication Projet Projet

Gland Instance Segmentation by Deep Multichannel Side Supervision

Eric Chang

January 2016

Publication Projet

Improving Indoor Mobility of the Visually Impaired with Depth-Based Spatial Sound

Simon Blessenohl, Cecily Morrison, Antonio Criminisi, Jamie Shotton

ICCV-ACVR workshop | December 2015

DOI PDF PDF Publication Projet

Spectral Forests: Learning of Surface Data, Application to Cortical Parcellation

Herve Lombaert, Antonio Criminisi, Nicholas Ayache

Medical Image Computing and Computer Assisted Intervention (MICCAI) | October 2015

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Prediction of expanded disability status scale subscores of motor dysfunction in multiple sclerosis using depth-sensing computer vision

M. D'Souza, J. Burggraaff, P. Kontschieder, J. Dorn, C.P. Kamm, S. Seinheimer, P. Tewarie, C. Morrison, Abigail Sellen, Antonio Criminisi, F. Dahlke, B Uitdehaag, L. Kappos

Multiple Sclerosis Journal | October 2015, Vol 21: pp. 409-409

Publication Projet

Video-based paired-comparison ranking: a validation tool for fine-grained measurements of motor dysfunction in multiple sclerosis

J. Burggraaff, J. Dorn, M. D'Souza, C. P. Kamm, P. Tewarie, P. Kontschieder, Cecily Morrison, A. Criminisi, F. Dahlke, L. Kappos, B. M. J. Uitdehaag, Antonio Criminisi , Abigail Sellen

Multiple Sclerosis Journal | September 2015, Vol 21: pp. 127-128

Publication Projet

Finetuned convolutional neural nets for cardiac MRI acquisition plane recognition

J. Margeta, Antonio Criminisi, R. Cabrera Lozoya, D. C. Lee, N. Ayache

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization | June 2015

Publication Publication Projet

Deep Convolutional Activation Features for Large Scale Brain Tumor Histopathology Image Classification and Segmentation

Eric Chang

January 2015

Publication Projet

Exploring Scalable Medical Image Encoders Beyond Text Supervision

Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Matthew P Lungren, Noel Codella, Stephanie Hyland, Javier Alvarez-Valle, Ozan Oktay

Nature Machine Intelligence | January 2025, Vol 7: pp. 119-130

Publication DOI Télécharger Projet

MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models

Harshita Sharma, Valentina Salvatelli, Shaury Srivastav, Kenza Bouzid, Shruthi Bannur, Daniel Coelho de Castro, Maximilian Ilse, Sam Bond-Taylor, Mercy Ranjit, Fabian Falck, Fernando Pérez-García, Anton Schwaighofer, Hannah Richardson (nee Murfet), Maria Teodora Wetscherek, Stephanie Hyland, Javier Alvarez-Valle

Machine Learning for Health Symposium 2024 | December 2024

Publication Preprint Projet

MAIRA-2: Grounded Radiology Report Generation

Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Anton Schwaighofer, Sam Bond-Taylor, Maximilian Ilse, Fernando Pérez-García, Valentina Salvatelli, Harshita Sharma, Felix Meissen, Mercy Ranjit, Shaury Srivastav, Julia Gong, Fabian Falck, Ozan Oktay, Anja Thieme, Matthew P Lungren, Maria Teodora Wetscherek, Javier Alvarez-Valle, Stephanie Hyland

MSR-TR-2024-18 | June 2024

Publié par Microsoft

Preprint PDF Github Télécharger Projet

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme

CHI 2024 | May 2024

Preprint Publication Projet

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology

Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob

2405.05299 | May 2024

Publié par arXiv

Preprint PDF Projet

Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology

Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle

Nature Communications | March 2024, Vol 15

DOI Publication PDF

RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing

Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse

ECCV 2024 | December 2023

Publication DOI Preprint Projet

MAIRA-1: A specialised large multimodal model for radiology report generation

Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Mercy Ranjit, Anton Schwaighofer, Fernando Pérez-García, Valentina Salvatelli, Shaury Srivastav, Anja Thieme, Noel Codella, Matthew P Lungren, Maria Teodora Wetscherek, Ozan Oktay, Javier Alvarez-Valle

MSR-TR-2023-47 | November 2023

Publié par Microsoft

Publication Projet

Exploring the Boundaries of GPT-4 in Radiology

Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle

EMNLP 2023 | October 2023

PDF Publication Projet

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay

The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023

Preprint Télécharger Projet

Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward

Anja Thieme, Aditya Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger

CHI 2023 | April 2023

Publication Projet

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay

The European Conference on Computer Vision (ECCV) | October 2022

Preprint Vidéo Télécharger Télécharger Projet

Active label cleaning for improved dataset quality under resource constraints

Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay

Nature Communications | March 2022, Vol 13(1161): pp. 1-11

Publication Github Projet Projet

fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data

Ruiyang Zhao, Burhaneddin Yaman, Yuxin Zhang, Russell Stewart, Austin Dixon, Florian Knoll, Zhengnan Huang, Yvonne W. Lui, Michael Hansen, Matthew P. Lungren

arXiv: Computer Vision and Pattern Recognition | September 2021, Vol arXiv:2109.03812

Publication Github Projet

Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs

Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro

ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021

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Addressing the Exorbitant Cost of Labeling Medical Images with Active Learning

Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

International Conference on Machine Learning in Medical Imaging and Analysis | June 2021

Best Presentation Award

Publication Projet

Automated Deep Segmentation of Healthy Organs in PSMA PET/CT Images

Ivan Klyuzhin, Guillaume Chausse, Ingrid Bloise, Juan M. Lavista Ferres, Carlos Uribe, Arman Rahmim

Journal of Nuclear Medicine | May 2021

Publication Projet

Secure Medical Image Analysis with CrypTFlow

Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare

NeurIPS PPML Workshop | December 2020

Publication Projet Projet

Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers

Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori

JAMA | November 2020

Publication Vidéo Github Projet

Deep Learning with Mixed Supervision for Brain Tumor Segmentation

Pawel Mlynarski, Herve' Delingette, Antonio Criminisi, Nicholas Ayache

December 2018

Publication Projet

Autofocus Layer for Semantic Segmentation

Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya Nori

International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI) | September 2018

DOI Publication Projet

Semi-Supervised Learning via Compact Latent Space Clustering

Konstantinos Kamnitsas, Daniel C. Castro, Loic Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya Nori

International Conference on Machine Learning (ICML) | June 2018

Publication Publication Projet

Unsupervised domain adaptation in brain lesion segmentation with adversarial networks

Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia F.J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker

Information Processing in Medical Imaging (IPMI) | June 2017

Publication Projet

Spectral Kernels for Probabilistic Analysis and Clustering of Shapes

Loic Le Folgoc, Aditya Nori, Antonio Criminisi

Information Processing in Medical Imaging (IPMI) | June 2017

DOI PDF Publication Projet

Lifted Auto-Context Forests for Brain Tumour Segmentation

Loic Le Folgoc, Aditya Nori, Siddharth Ancha, Antonio Criminisi

MICCAI Brain Lesion Workshop | October 2016

DOI PDF Publication Projet

DeepMedic for Brain Tumor Segmentation

Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker

MICCAI Brain Lesion Workshop | October 2016

DOI PDF Publication Projet

Generalisability of Image Quality Transfer: Can we approximate in-vivo human brains from dead monkey brains?

Aurobrata Ghosh, V. Wottschel, Enrico Kaden, H. Zhang, Stamatios N. Sotiropoulos, D. Zikic, T. B. Dyrby, Antonio Criminisi, Daniel C. Alexander

April 2016

Publication Projet Projet

Decision Forests, Convolutional Networks and the Models in-Between

Yani Ioannou, Duncan Robertson, D. Zikic, Peter Kontschieder, Jamie Shotton, Matthew Brown, Antonio Criminisi

March 2016

DOI Publication Projet Projet

Improving Indoor Mobility of the Visually Impaired with Depth-Based Spatial Sound

Simon Blessenohl, Cecily Morrison, Antonio Criminisi, Jamie Shotton

ICCV-ACVR workshop | December 2015

DOI PDF PDF Publication Projet

Spectral Forests: Learning of Surface Data, Application to Cortical Parcellation

Herve Lombaert, Antonio Criminisi, Nicholas Ayache

Medical Image Computing and Computer Assisted Intervention (MICCAI) | October 2015

DOI PDF Publication Projet Projet

Prediction of expanded disability status scale subscores of motor dysfunction in multiple sclerosis using depth-sensing computer vision

M. D'Souza, J. Burggraaff, P. Kontschieder, J. Dorn, C.P. Kamm, S. Seinheimer, P. Tewarie, C. Morrison, Abigail Sellen, Antonio Criminisi, F. Dahlke, B Uitdehaag, L. Kappos

Multiple Sclerosis Journal | October 2015, Vol 21: pp. 409-409

Publication Projet

Video-based paired-comparison ranking: a validation tool for fine-grained measurements of motor dysfunction in multiple sclerosis

J. Burggraaff, J. Dorn, M. D'Souza, C. P. Kamm, P. Tewarie, P. Kontschieder, Cecily Morrison, A. Criminisi, F. Dahlke, L. Kappos, B. M. J. Uitdehaag, Antonio Criminisi , Abigail Sellen

Multiple Sclerosis Journal | September 2015, Vol 21: pp. 127-128

Publication Projet

Finetuned convolutional neural nets for cardiac MRI acquisition plane recognition

J. Margeta, Antonio Criminisi, R. Cabrera Lozoya, D. C. Lee, N. Ayache

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization | June 2015

Publication Publication Projet

Exploring Scalable Medical Image Encoders Beyond Text Supervision

Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Matthew P Lungren, Noel Codella, Stephanie Hyland, Javier Alvarez-Valle, Ozan Oktay

Nature Machine Intelligence | January 2025, Vol 7: pp. 119-130

Publication DOI Télécharger Projet

MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models

Harshita Sharma, Valentina Salvatelli, Shaury Srivastav, Kenza Bouzid, Shruthi Bannur, Daniel Coelho de Castro, Maximilian Ilse, Sam Bond-Taylor, Mercy Ranjit, Fabian Falck, Fernando Pérez-García, Anton Schwaighofer, Hannah Richardson (nee Murfet), Maria Teodora Wetscherek, Stephanie Hyland, Javier Alvarez-Valle

Machine Learning for Health Symposium 2024 | December 2024

Publication Preprint Projet

OSAIRIS: Lessons Learned from the Hospital-Based Implementation and Evaluation of an Open-Source Deep-Learning Model for Radiotherapy Image Segmentation

Alexandra Constantinou, Andrew Hoole, David C. Wong, G. S. Sagoo, Javier Alvarez-Valle, Kenji Takeda, Tom Griffiths, Amy Edwards, Andrew Robinson, Liam Stubbington, Niall Bolger, Yvonne Rimmer, Thiraviyam Elumalai, K. T. Jayaprakash, Richard Benson, Ian Gleeson, Rebecca Sen, Louisa Stockton, Tian Wang, Stephanie Brown, E. Gatfield, C. Sanghera, Alexandros Mourounas, Barry Evans, Anita Anthony, Renteng Hou, Marian Toomey, K. Wildschut, Aviva Grisby, Gill Barnett, Rose McMullen, Raj Jena

Clinical Oncology | October 2024

DOI Github Github Github Github Projet Projet

MAIRA-2: Grounded Radiology Report Generation

Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Anton Schwaighofer, Sam Bond-Taylor, Maximilian Ilse, Fernando Pérez-García, Valentina Salvatelli, Harshita Sharma, Felix Meissen, Mercy Ranjit, Shaury Srivastav, Julia Gong, Fabian Falck, Ozan Oktay, Anja Thieme, Matthew P Lungren, Maria Teodora Wetscherek, Javier Alvarez-Valle, Stephanie Hyland

MSR-TR-2024-18 | June 2024

Publié par Microsoft

Preprint PDF Github Télécharger Projet

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology

Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob

2405.05299 | May 2024

Publié par arXiv

Preprint PDF Projet

Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology

Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle

Nature Communications | March 2024, Vol 15

DOI Publication PDF

RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing

Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse

ECCV 2024 | December 2023

Publication DOI Preprint Projet

Exploring the Boundaries of GPT-4 in Radiology

Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle

EMNLP 2023 | October 2023

PDF Publication Projet

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay

The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023

Preprint Télécharger Projet

Deep Learning Models for COVID-19 Chest X-ray Classification: Preventing Shortcut Learning Using Feature Disentanglement

Caleb Robinson, Anusua Trivedi, Marian Blazes, Anthony Ortiz, Jocelyn Desbiens, Sunil Gupta, Rahul Dodhia, Pavan K Bhatraju, W Conrad Liles, Aaron Lee, Jayashree Kalpathy-Cramer, Juan M. Lavista Ferres

PLOS | October 2022

Publication PDF Projet Projet

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay

The European Conference on Computer Vision (ECCV) | October 2022

Preprint Vidéo Télécharger Télécharger Projet

Active label cleaning for improved dataset quality under resource constraints

Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay

Nature Communications | March 2022, Vol 13(1161): pp. 1-11

Publication Github Projet Projet

Effective Deep Learning Approaches for Predicting COVID-19 Outcomes from Chest Computed Tomography Volumes

Anusua Trivedi, Anthony Ortiz, Caleb Robinson, Jocelyn Desbiens, Marian Blazes, Sunil Gupta, Rahul Dodhia, Pavan Bhatraju, W Conrad Liles, Aaron Lee, Juan M. Lavista Ferres

Nature Scientific Reports | February 2022

Publication PDF Projet Projet

Machine Learning for Auto-Segmentation in Radiotherapy Planning

K Harrison, H Pullen, C Welsh, Ozan Oktay, Javier Alvarez-Valle, R Jena

The Royal College of Radiologists – Clinical Oncology | January 2022, Vol 34(2): pp. 74-88

Publication Projet Projet

Sociodemographic and clinical features predictive of SARS-CoV-2 test positivity across healthcare visit-types

Jimmy Phuong, Stephanie Hyland, Stephen J. Mooney, Dustin R. Long, Kenji Takeda, Monica S. Vavilala, Kenton O’Hara

PLOS ONE | October 2021

Publication Projet

fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data

Ruiyang Zhao, Burhaneddin Yaman, Yuxin Zhang, Russell Stewart, Austin Dixon, Florian Knoll, Zhengnan Huang, Yvonne W. Lui, Michael Hansen, Matthew P. Lungren

arXiv: Computer Vision and Pattern Recognition | September 2021, Vol arXiv:2109.03812

Publication Github Projet

Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs

Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro

ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021

PDF Preprint Projet Projet Projet Projet

Addressing the Exorbitant Cost of Labeling Medical Images with Active Learning

Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

International Conference on Machine Learning in Medical Imaging and Analysis | June 2021

Best Presentation Award

Publication Projet

Automated Deep Segmentation of Healthy Organs in PSMA PET/CT Images

Ivan Klyuzhin, Guillaume Chausse, Ingrid Bloise, Juan M. Lavista Ferres, Carlos Uribe, Arman Rahmim

Journal of Nuclear Medicine | May 2021

Publication Projet

Secure Medical Image Analysis with CrypTFlow

Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare

NeurIPS PPML Workshop | December 2020

Publication Projet Projet

Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers

Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori

JAMA | November 2020

Publication Vidéo Github Projet

Binary Mode Multinomial Deep Learning Model for more efficient Automated Diabetic Retinopathy Detection

Anusua Trivedi, J. Desbiens, Ron Gross, S. Gupta, Juan M. Lavista Ferres, Rahul Dodhia

NeurIPS 2019 | December 2019

PDF Projet

Unsupervised Learning for Cell-level Visual Representation in Histopathology Images with Generative Adversarial Networks

Bo Hu, Ye Tang, Eric Chang, Yubo Fan, Maode Lai, Yan Xu

IEEE Journal of Biomedical and Health Informatics | May 2019

Publication Projet

Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge

Mitko Veta, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A. Shah, Dayong Wang, Mikael Rousson, Martin Hedlund, David Tellez, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Viana, Vassili Kovalev, Vitali Liauchuk, Hady Ahmady Phoulady, Talha Qaiser, Simon Graham, Nasir Rajpoot, Erik Sjöblom, Jesper Molin, Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Zhipeng Jia, Eric Chang, Yan Xu, Andrew H. Beck, Paul J. van Diest, Josien P. W. Pluim

Medical Image Analysis | March 2019

Publication Projet

Unsupervised 3D End-to-End Medical Image Registration with Volume Tweening Network

Tingfung Lau, Ji Luo, Shengyu Zhao, Eric Chang, Yan Xu

February 2019

Publication Projet

3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context

Pawel Mlynarski, Herve' Delingette, Antonio Criminisi, Nicholas Ayache

Computerized Medical Imaging and Graphics | February 2019

Publication Projet

Deep Learning with Mixed Supervision for Brain Tumor Segmentation

Pawel Mlynarski, Herve' Delingette, Antonio Criminisi, Nicholas Ayache

December 2018

Publication Projet

Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features

M. W. Macomber, M. H. Phillips, Ivan Tarapov, R. Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, M. J. Nyflot

Physics in Medicine and Biology | November 2018, Vol 63(23): pp. 235002-235002

DOI PDF Publication

Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features

Meghan W Macomber, Mark Phillips, Ivan Tarapov, Rajesh Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, Matthew J Nyflot

Physics in Medicine & Biology | November 2018, Vol 63(23)

Publication Projet

MRI Image-to-Image Translation for Cross-Modality Image Registration and Segmentation

Qianye Yang, Nannan Li, Zixu Zhao, Xingyu Fan, Eric Chang, Yan Xu

January 2018

Publication Projet

Unsupervised End-to-end Learning for Deformable Medical Image Registration

Siyuan Shan, Wen Yan, Xiaoqing Guo, Eric Chang, Yubo Fan, Yan Xu

January 2018

Publication Projet

Gland instance segmentation using deep multichannel neural networks

Yan Xu, Yang Li, Yipei Wang, Mingyuan Liu, Yubo Fan, Maode Lai, Eric Chang

IEEE Transactions on Biomedical Engineering | December 2017

Publication Projet

Constrained Deep Weak Supervision for Histopathology Image Segmentation

Zhipeng Jia, Xingyi Huang, Eric Chang, Yan Xu

IEEE Transactions on Medical Imaging | November 2017

Publication Projet

Parallel multiple instance learning for extremely large histopathology image analysis

Yan Xu, Yeshu Li, Zhengyang Shen, Ziwei Wu, Teng Gao, Yubo Fan, Maode Lai, Eric Chang

BMC bioinformatics | August 2017

Publication Projet

Unsupervised domain adaptation in brain lesion segmentation with adversarial networks

Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia F.J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker

Information Processing in Medical Imaging (IPMI) | June 2017

Publication Projet

Spectral Kernels for Probabilistic Analysis and Clustering of Shapes

Loic Le Folgoc, Aditya Nori, Antonio Criminisi

Information Processing in Medical Imaging (IPMI) | June 2017

DOI PDF Publication Projet

Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features

Yan Xu, Zhipeng Jia, Liang-Bo Wang, Yuqing Ai, Fang Zhang, Maode Lai, Eric Chang

Bmc Bioinformatics | May 2017

Publication Projet

Image Quality Transfer and Applications in Diffusion MRI

Daniel C. Alexander, Darko Zikic, Aurobrata Gosh, Ryutaro Tanno, Viktor Wottschel, Jiaying Zhang, Enrico Kaden, Tim B. Dirby, Stamatios N. Sotiropoulos, Hui Zhang, Antonio Criminisi

Neuroimage | March 2017

Publication Projet

Sparse Bayesian registration of medical images for self-tuning of parameters and spatially adaptive parametrization of displacements.

Loic Le Folgoc, Hervé Delingette, Antonio Criminisi, Nicholas Ayache

Medical Image Analysis | January 2017, Vol 36: pp. 79-97

PDF DOI Projet

Quantifying Registration Uncertainty with Sparse Bayesian Modeling

Loic Le Folgoc, Hervé Delingette, Antonio Criminisi, Nicholas Ayache

IEEE Transactions on Medical Imaging | December 2016

Publication Projet

Lifted Auto-Context Forests for Brain Tumour Segmentation

Loic Le Folgoc, Aditya Nori, Siddharth Ancha, Antonio Criminisi

MICCAI Brain Lesion Workshop | October 2016

DOI PDF Publication Projet

DeepMedic for Brain Tumor Segmentation

Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker

MICCAI Brain Lesion Workshop | October 2016

DOI PDF Publication Projet

3D-SIFT-Flow for atlas-based CT liver image segmentation

Yan Xu, Chenchao Xu, Xiao Kuang, Hongkai Wang, Eric Chang, Weimin Huang, Yubo Fan

January 2016

Publication Projet

Gland Instance Segmentation by Deep Multichannel Side Supervision

Eric Chang

January 2016

Publication Projet

Deep Convolutional Activation Features for Large Scale Brain Tumor Histopathology Image Classification and Segmentation

Eric Chang

January 2015

Publication Projet

Exploring Scalable Medical Image Encoders Beyond Text Supervision

Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Matthew P Lungren, Noel Codella, Stephanie Hyland, Javier Alvarez-Valle, Ozan Oktay

Nature Machine Intelligence | January 2025, Vol 7: pp. 119-130

Publication DOI Télécharger Projet

RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing

Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse

ECCV 2024 | December 2023

Publication DOI Preprint Projet

MAIRA-1: A specialised large multimodal model for radiology report generation

Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Mercy Ranjit, Anton Schwaighofer, Fernando Pérez-García, Valentina Salvatelli, Shaury Srivastav, Anja Thieme, Noel Codella, Matthew P Lungren, Maria Teodora Wetscherek, Ozan Oktay, Javier Alvarez-Valle

MSR-TR-2023-47 | November 2023

Publié par Microsoft

Publication Projet

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay

The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023

Preprint Télécharger Projet

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay

The European Conference on Computer Vision (ECCV) | October 2022

Preprint Vidéo Télécharger Télécharger Projet

Active label cleaning for improved dataset quality under resource constraints

Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay

Nature Communications | March 2022, Vol 13(1161): pp. 1-11

Publication Github Projet Projet

Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs

Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro

ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021

PDF Preprint Projet Projet Projet Projet

Addressing the Exorbitant Cost of Labeling Medical Images with Active Learning

Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

International Conference on Machine Learning in Medical Imaging and Analysis | June 2021

Best Presentation Award

Publication Projet

Deep Learning with Mixed Supervision for Brain Tumor Segmentation

Pawel Mlynarski, Herve' Delingette, Antonio Criminisi, Nicholas Ayache

December 2018

Publication Projet

Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features

M. W. Macomber, M. H. Phillips, Ivan Tarapov, R. Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, M. J. Nyflot

Physics in Medicine and Biology | November 2018, Vol 63(23): pp. 235002-235002

DOI PDF Publication

Image Quality Transfer and Applications in Diffusion MRI

Daniel C. Alexander, Darko Zikic, Aurobrata Gosh, Ryutaro Tanno, Viktor Wottschel, Jiaying Zhang, Enrico Kaden, Tim B. Dirby, Stamatios N. Sotiropoulos, Hui Zhang, Antonio Criminisi

Neuroimage | March 2017

Publication Projet

Sparse Bayesian registration of medical images for self-tuning of parameters and spatially adaptive parametrization of displacements.

Loic Le Folgoc, Hervé Delingette, Antonio Criminisi, Nicholas Ayache

Medical Image Analysis | January 2017, Vol 36: pp. 79-97

PDF DOI Projet

Quantifying Registration Uncertainty with Sparse Bayesian Modeling

Loic Le Folgoc, Hervé Delingette, Antonio Criminisi, Nicholas Ayache

IEEE Transactions on Medical Imaging | December 2016

Publication Projet

Generalisability of Image Quality Transfer: Can we approximate in-vivo human brains from dead monkey brains?

Aurobrata Ghosh, V. Wottschel, Enrico Kaden, H. Zhang, Stamatios N. Sotiropoulos, D. Zikic, T. B. Dyrby, Antonio Criminisi, Daniel C. Alexander

April 2016

Publication Projet Projet

Decision Forests, Convolutional Networks and the Models in-Between

Yani Ioannou, Duncan Robertson, D. Zikic, Peter Kontschieder, Jamie Shotton, Matthew Brown, Antonio Criminisi

March 2016

DOI Publication Projet Projet

Assessing Multiple Sclerosis with Kinect: Designing Computer Vision Systems for Real-World Use

Cecily Morrison, Kit Huckvale, Bob Corish, Jonas Dorn, Peter Kontschieder, Kenton O'Hara, ASSESS MS Team, Antonio Criminisi, Abigail Sellen

Human-Computer Interaction | January 2016

Publication Publication Projet Projet

Improving Indoor Mobility of the Visually Impaired with Depth-Based Spatial Sound

Simon Blessenohl, Cecily Morrison, Antonio Criminisi, Jamie Shotton

ICCV-ACVR workshop | December 2015

DOI PDF PDF Publication Projet

Spectral Forests: Learning of Surface Data, Application to Cortical Parcellation

Herve Lombaert, Antonio Criminisi, Nicholas Ayache

Medical Image Computing and Computer Assisted Intervention (MICCAI) | October 2015

DOI PDF Publication Projet Projet

Prediction of expanded disability status scale subscores of motor dysfunction in multiple sclerosis using depth-sensing computer vision

M. D'Souza, J. Burggraaff, P. Kontschieder, J. Dorn, C.P. Kamm, S. Seinheimer, P. Tewarie, C. Morrison, Abigail Sellen, Antonio Criminisi, F. Dahlke, B Uitdehaag, L. Kappos

Multiple Sclerosis Journal | October 2015, Vol 21: pp. 409-409

Publication Projet

Video-based paired-comparison ranking: a validation tool for fine-grained measurements of motor dysfunction in multiple sclerosis

J. Burggraaff, J. Dorn, M. D'Souza, C. P. Kamm, P. Tewarie, P. Kontschieder, Cecily Morrison, A. Criminisi, F. Dahlke, L. Kappos, B. M. J. Uitdehaag, Antonio Criminisi , Abigail Sellen

Multiple Sclerosis Journal | September 2015, Vol 21: pp. 127-128

Publication Projet

Finetuned convolutional neural nets for cardiac MRI acquisition plane recognition

J. Margeta, Antonio Criminisi, R. Cabrera Lozoya, D. C. Lee, N. Ayache

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization | June 2015

Publication Publication Projet

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme

CHI 2024 | May 2024

Preprint Publication Projet

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology

Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob

2405.05299 | May 2024

Publié par arXiv

Preprint PDF Projet

Using Thematic Analysis in Healthcare HCI at CHI: A Scoping Review

Robert Bowman, Camille Nadal, Kellie Morrissey, Anja Thieme, Gavin Doherty

CHI 2023 | April 2023

Publication

Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward

Anja Thieme, Aditya Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger

CHI 2023 | April 2023

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Assessing Multiple Sclerosis with Kinect: Designing Computer Vision Systems for Real-World Use

Cecily Morrison, Kit Huckvale, Bob Corish, Jonas Dorn, Peter Kontschieder, Kenton O'Hara, ASSESS MS Team, Antonio Criminisi, Abigail Sellen

Human-Computer Interaction | January 2016

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Prediction of expanded disability status scale subscores of motor dysfunction in multiple sclerosis using depth-sensing computer vision

M. D'Souza, J. Burggraaff, P. Kontschieder, J. Dorn, C.P. Kamm, S. Seinheimer, P. Tewarie, C. Morrison, Abigail Sellen, Antonio Criminisi, F. Dahlke, B Uitdehaag, L. Kappos

Multiple Sclerosis Journal | October 2015, Vol 21: pp. 409-409

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Video-based paired-comparison ranking: a validation tool for fine-grained measurements of motor dysfunction in multiple sclerosis

J. Burggraaff, J. Dorn, M. D'Souza, C. P. Kamm, P. Tewarie, P. Kontschieder, Cecily Morrison, A. Criminisi, F. Dahlke, L. Kappos, B. M. J. Uitdehaag, Antonio Criminisi , Abigail Sellen

Multiple Sclerosis Journal | September 2015, Vol 21: pp. 127-128

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Secure Medical Image Analysis with CrypTFlow

Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare

NeurIPS PPML Workshop | December 2020

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Secure Medical Image Analysis with CrypTFlow

Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare

NeurIPS PPML Workshop | December 2020

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MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models

Harshita Sharma, Valentina Salvatelli, Shaury Srivastav, Kenza Bouzid, Shruthi Bannur, Daniel Coelho de Castro, Maximilian Ilse, Sam Bond-Taylor, Mercy Ranjit, Fabian Falck, Fernando Pérez-García, Anton Schwaighofer, Hannah Richardson (nee Murfet), Maria Teodora Wetscherek, Stephanie Hyland, Javier Alvarez-Valle

Machine Learning for Health Symposium 2024 | December 2024

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Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme

CHI 2024 | May 2024

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RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing

Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse

ECCV 2024 | December 2023

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Exploring the Boundaries of GPT-4 in Radiology

Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle

EMNLP 2023 | October 2023

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Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay

The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023

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Using Thematic Analysis in Healthcare HCI at CHI: A Scoping Review

Robert Bowman, Camille Nadal, Kellie Morrissey, Anja Thieme, Gavin Doherty

CHI 2023 | April 2023

Publication

Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward

Anja Thieme, Aditya Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger

CHI 2023 | April 2023

Publication Projet

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay

The European Conference on Computer Vision (ECCV) | October 2022

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Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs

Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro

ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021

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Addressing the Exorbitant Cost of Labeling Medical Images with Active Learning

Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

International Conference on Machine Learning in Medical Imaging and Analysis | June 2021

Best Presentation Award

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Secure Medical Image Analysis with CrypTFlow

Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare

NeurIPS PPML Workshop | December 2020

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Binary Mode Multinomial Deep Learning Model for more efficient Automated Diabetic Retinopathy Detection

Anusua Trivedi, J. Desbiens, Ron Gross, S. Gupta, Juan M. Lavista Ferres, Rahul Dodhia

NeurIPS 2019 | December 2019

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Autofocus Layer for Semantic Segmentation

Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya Nori

International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI) | September 2018

DOI Publication Projet

Semi-Supervised Learning via Compact Latent Space Clustering

Konstantinos Kamnitsas, Daniel C. Castro, Loic Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya Nori

International Conference on Machine Learning (ICML) | June 2018

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Unsupervised domain adaptation in brain lesion segmentation with adversarial networks

Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia F.J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker

Information Processing in Medical Imaging (IPMI) | June 2017

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Spectral Kernels for Probabilistic Analysis and Clustering of Shapes

Loic Le Folgoc, Aditya Nori, Antonio Criminisi

Information Processing in Medical Imaging (IPMI) | June 2017

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Lifted Auto-Context Forests for Brain Tumour Segmentation

Loic Le Folgoc, Aditya Nori, Siddharth Ancha, Antonio Criminisi

MICCAI Brain Lesion Workshop | October 2016

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DeepMedic for Brain Tumor Segmentation

Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker

MICCAI Brain Lesion Workshop | October 2016

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3D-SIFT-Flow for atlas-based CT liver image segmentation

Yan Xu, Chenchao Xu, Xiao Kuang, Hongkai Wang, Eric Chang, Weimin Huang, Yubo Fan

January 2016

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Gland Instance Segmentation by Deep Multichannel Side Supervision

Eric Chang

January 2016

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Improving Indoor Mobility of the Visually Impaired with Depth-Based Spatial Sound

Simon Blessenohl, Cecily Morrison, Antonio Criminisi, Jamie Shotton

ICCV-ACVR workshop | December 2015

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Spectral Forests: Learning of Surface Data, Application to Cortical Parcellation

Herve Lombaert, Antonio Criminisi, Nicholas Ayache

Medical Image Computing and Computer Assisted Intervention (MICCAI) | October 2015

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Deep Convolutional Activation Features for Large Scale Brain Tumor Histopathology Image Classification and Segmentation

Eric Chang

January 2015

Publication Projet

Exploring Scalable Medical Image Encoders Beyond Text Supervision

Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Matthew P Lungren, Noel Codella, Stephanie Hyland, Javier Alvarez-Valle, Ozan Oktay

Nature Machine Intelligence | January 2025, Vol 7: pp. 119-130

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OSAIRIS: Lessons Learned from the Hospital-Based Implementation and Evaluation of an Open-Source Deep-Learning Model for Radiotherapy Image Segmentation

Alexandra Constantinou, Andrew Hoole, David C. Wong, G. S. Sagoo, Javier Alvarez-Valle, Kenji Takeda, Tom Griffiths, Amy Edwards, Andrew Robinson, Liam Stubbington, Niall Bolger, Yvonne Rimmer, Thiraviyam Elumalai, K. T. Jayaprakash, Richard Benson, Ian Gleeson, Rebecca Sen, Louisa Stockton, Tian Wang, Stephanie Brown, E. Gatfield, C. Sanghera, Alexandros Mourounas, Barry Evans, Anita Anthony, Renteng Hou, Marian Toomey, K. Wildschut, Aviva Grisby, Gill Barnett, Rose McMullen, Raj Jena

Clinical Oncology | October 2024

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Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology

Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle

Nature Communications | March 2024, Vol 15

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Deep Learning Models for COVID-19 Chest X-ray Classification: Preventing Shortcut Learning Using Feature Disentanglement

Caleb Robinson, Anusua Trivedi, Marian Blazes, Anthony Ortiz, Jocelyn Desbiens, Sunil Gupta, Rahul Dodhia, Pavan K Bhatraju, W Conrad Liles, Aaron Lee, Jayashree Kalpathy-Cramer, Juan M. Lavista Ferres

PLOS | October 2022

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Active label cleaning for improved dataset quality under resource constraints

Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay

Nature Communications | March 2022, Vol 13(1161): pp. 1-11

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Effective Deep Learning Approaches for Predicting COVID-19 Outcomes from Chest Computed Tomography Volumes

Anusua Trivedi, Anthony Ortiz, Caleb Robinson, Jocelyn Desbiens, Marian Blazes, Sunil Gupta, Rahul Dodhia, Pavan Bhatraju, W Conrad Liles, Aaron Lee, Juan M. Lavista Ferres

Nature Scientific Reports | February 2022

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Machine Learning for Auto-Segmentation in Radiotherapy Planning

K Harrison, H Pullen, C Welsh, Ozan Oktay, Javier Alvarez-Valle, R Jena

The Royal College of Radiologists – Clinical Oncology | January 2022, Vol 34(2): pp. 74-88

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Sociodemographic and clinical features predictive of SARS-CoV-2 test positivity across healthcare visit-types

Jimmy Phuong, Stephanie Hyland, Stephen J. Mooney, Dustin R. Long, Kenji Takeda, Monica S. Vavilala, Kenton O’Hara

PLOS ONE | October 2021

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fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data

Ruiyang Zhao, Burhaneddin Yaman, Yuxin Zhang, Russell Stewart, Austin Dixon, Florian Knoll, Zhengnan Huang, Yvonne W. Lui, Michael Hansen, Matthew P. Lungren

arXiv: Computer Vision and Pattern Recognition | September 2021, Vol arXiv:2109.03812

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Automated Deep Segmentation of Healthy Organs in PSMA PET/CT Images

Ivan Klyuzhin, Guillaume Chausse, Ingrid Bloise, Juan M. Lavista Ferres, Carlos Uribe, Arman Rahmim

Journal of Nuclear Medicine | May 2021

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Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers

Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori

JAMA | November 2020

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Unsupervised Learning for Cell-level Visual Representation in Histopathology Images with Generative Adversarial Networks

Bo Hu, Ye Tang, Eric Chang, Yubo Fan, Maode Lai, Yan Xu

IEEE Journal of Biomedical and Health Informatics | May 2019

Publication Projet

Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge

Mitko Veta, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A. Shah, Dayong Wang, Mikael Rousson, Martin Hedlund, David Tellez, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Viana, Vassili Kovalev, Vitali Liauchuk, Hady Ahmady Phoulady, Talha Qaiser, Simon Graham, Nasir Rajpoot, Erik Sjöblom, Jesper Molin, Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Zhipeng Jia, Eric Chang, Yan Xu, Andrew H. Beck, Paul J. van Diest, Josien P. W. Pluim

Medical Image Analysis | March 2019

Publication Projet

3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context

Pawel Mlynarski, Herve' Delingette, Antonio Criminisi, Nicholas Ayache

Computerized Medical Imaging and Graphics | February 2019

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Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features

M. W. Macomber, M. H. Phillips, Ivan Tarapov, R. Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, M. J. Nyflot

Physics in Medicine and Biology | November 2018, Vol 63(23): pp. 235002-235002

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Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features

Meghan W Macomber, Mark Phillips, Ivan Tarapov, Rajesh Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, Matthew J Nyflot

Physics in Medicine & Biology | November 2018, Vol 63(23)

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Gland instance segmentation using deep multichannel neural networks

Yan Xu, Yang Li, Yipei Wang, Mingyuan Liu, Yubo Fan, Maode Lai, Eric Chang

IEEE Transactions on Biomedical Engineering | December 2017

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Constrained Deep Weak Supervision for Histopathology Image Segmentation

Zhipeng Jia, Xingyi Huang, Eric Chang, Yan Xu

IEEE Transactions on Medical Imaging | November 2017

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Parallel multiple instance learning for extremely large histopathology image analysis

Yan Xu, Yeshu Li, Zhengyang Shen, Ziwei Wu, Teng Gao, Yubo Fan, Maode Lai, Eric Chang

BMC bioinformatics | August 2017

Publication Projet

Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features

Yan Xu, Zhipeng Jia, Liang-Bo Wang, Yuqing Ai, Fang Zhang, Maode Lai, Eric Chang

Bmc Bioinformatics | May 2017

Publication Projet

Image Quality Transfer and Applications in Diffusion MRI

Daniel C. Alexander, Darko Zikic, Aurobrata Gosh, Ryutaro Tanno, Viktor Wottschel, Jiaying Zhang, Enrico Kaden, Tim B. Dirby, Stamatios N. Sotiropoulos, Hui Zhang, Antonio Criminisi

Neuroimage | March 2017

Publication Projet

Sparse Bayesian registration of medical images for self-tuning of parameters and spatially adaptive parametrization of displacements.

Loic Le Folgoc, Hervé Delingette, Antonio Criminisi, Nicholas Ayache

Medical Image Analysis | January 2017, Vol 36: pp. 79-97

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Quantifying Registration Uncertainty with Sparse Bayesian Modeling

Loic Le Folgoc, Hervé Delingette, Antonio Criminisi, Nicholas Ayache

IEEE Transactions on Medical Imaging | December 2016

Publication Projet

Assessing Multiple Sclerosis with Kinect: Designing Computer Vision Systems for Real-World Use

Cecily Morrison, Kit Huckvale, Bob Corish, Jonas Dorn, Peter Kontschieder, Kenton O'Hara, ASSESS MS Team, Antonio Criminisi, Abigail Sellen

Human-Computer Interaction | January 2016

Publication Publication Projet Projet

Prediction of expanded disability status scale subscores of motor dysfunction in multiple sclerosis using depth-sensing computer vision

M. D'Souza, J. Burggraaff, P. Kontschieder, J. Dorn, C.P. Kamm, S. Seinheimer, P. Tewarie, C. Morrison, Abigail Sellen, Antonio Criminisi, F. Dahlke, B Uitdehaag, L. Kappos

Multiple Sclerosis Journal | October 2015, Vol 21: pp. 409-409

Publication Projet

Video-based paired-comparison ranking: a validation tool for fine-grained measurements of motor dysfunction in multiple sclerosis

J. Burggraaff, J. Dorn, M. D'Souza, C. P. Kamm, P. Tewarie, P. Kontschieder, Cecily Morrison, A. Criminisi, F. Dahlke, L. Kappos, B. M. J. Uitdehaag, Antonio Criminisi , Abigail Sellen

Multiple Sclerosis Journal | September 2015, Vol 21: pp. 127-128

Publication Projet

Finetuned convolutional neural nets for cardiac MRI acquisition plane recognition

J. Margeta, Antonio Criminisi, R. Cabrera Lozoya, D. C. Lee, N. Ayache

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization | June 2015

Publication Publication Projet

MAIRA-2: Grounded Radiology Report Generation

Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Anton Schwaighofer, Sam Bond-Taylor, Maximilian Ilse, Fernando Pérez-García, Valentina Salvatelli, Harshita Sharma, Felix Meissen, Mercy Ranjit, Shaury Srivastav, Julia Gong, Fabian Falck, Ozan Oktay, Anja Thieme, Matthew P Lungren, Maria Teodora Wetscherek, Javier Alvarez-Valle, Stephanie Hyland

MSR-TR-2024-18 | June 2024

Publié par Microsoft

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Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology

Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob

2405.05299 | May 2024

Publié par arXiv

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MAIRA-1: A specialised large multimodal model for radiology report generation

Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Mercy Ranjit, Anton Schwaighofer, Fernando Pérez-García, Valentina Salvatelli, Shaury Srivastav, Anja Thieme, Noel Codella, Matthew P Lungren, Maria Teodora Wetscherek, Ozan Oktay, Javier Alvarez-Valle

MSR-TR-2023-47 | November 2023

Publié par Microsoft

Publication Projet

Unsupervised 3D End-to-End Medical Image Registration with Volume Tweening Network

Tingfung Lau, Ji Luo, Shengyu Zhao, Eric Chang, Yan Xu

February 2019

Publication Projet

MRI Image-to-Image Translation for Cross-Modality Image Registration and Segmentation

Qianye Yang, Nannan Li, Zixu Zhao, Xingyu Fan, Eric Chang, Yan Xu

January 2018

Publication Projet

Unsupervised End-to-end Learning for Deformable Medical Image Registration

Siyuan Shan, Wen Yan, Xiaoqing Guo, Eric Chang, Yubo Fan, Yan Xu

January 2018

Publication Projet

Deep Learning with Mixed Supervision for Brain Tumor Segmentation

Pawel Mlynarski, Herve' Delingette, Antonio Criminisi, Nicholas Ayache

December 2018

Publication Projet

Generalisability of Image Quality Transfer: Can we approximate in-vivo human brains from dead monkey brains?

Aurobrata Ghosh, V. Wottschel, Enrico Kaden, H. Zhang, Stamatios N. Sotiropoulos, D. Zikic, T. B. Dyrby, Antonio Criminisi, Daniel C. Alexander

April 2016

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Decision Forests, Convolutional Networks and the Models in-Between

Yani Ioannou, Duncan Robertson, D. Zikic, Peter Kontschieder, Jamie Shotton, Matthew Brown, Antonio Criminisi

March 2016

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