Biomedical Imaging

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 Project

RAD-DINO: 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

MSR-TR-2024-5 | January 2024

Published by Microsoft

Preprint Project

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

Published by Microsoft

Publication Project

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 Project

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 Download Project

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

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

Publication PDF Project Project

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 Video Download Download Project

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 Project Project

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 Project Project

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 Project Project

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 Project

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 Project

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 Project Project Project Project

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 Project

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 Project

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 Project Project

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 Video Github Project

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 Project

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 Project

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 Project

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 Project

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 Project

Deep Learning with Mixed Supervision for Brain Tumor Segmentation

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

December 2018

Publication Project

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 Project

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 Project

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 Project

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 Project

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 Project

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 Project

Constrained Deep Weak Supervision for Histopathology Image Segmentation

Zhipeng Jia, Xingyi Huang, Eric Chang, Yan Xu

IEEE Transactions on Medical Imaging | November 2017

Publication Project

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 Project

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 Project

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 Project

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 Project

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 Project

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 Project

Quantifying Registration Uncertainty with Sparse Bayesian Modeling

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

IEEE Transactions on Medical Imaging | December 2016

Publication Project

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 Project

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 Project

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 Project Project

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 Project Project

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 Project

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 Project Project

Gland Instance Segmentation by Deep Multichannel Side Supervision

Eric Chang

January 2016

Publication Project

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 Project

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 Project Project

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 Project

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 Project

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 Project

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

Eric Chang

January 2015

Publication Project

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 Project

RAD-DINO: 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

MSR-TR-2024-5 | January 2024

Published by Microsoft

Preprint Project

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

Published by Microsoft

Publication Project

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 Project

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 Download Project

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

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 Video Download Download Project

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 Project Project

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 Project

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 Project Project Project Project

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 Project

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 Project

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 Project Project

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 Video Github Project

Deep Learning with Mixed Supervision for Brain Tumor Segmentation

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

December 2018

Publication Project

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 Project

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 Project

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 Project

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 Project

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 Project

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 Project

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 Project Project

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 Project Project

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 Project

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 Project Project

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 Project

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 Project

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 Project

RAD-DINO: 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

MSR-TR-2024-5 | January 2024

Published by Microsoft

Preprint Project

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

Published by Microsoft

Publication Project

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 Download Project

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 Video Download Download Project

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 Project Project

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 Project Project Project Project

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 Project

Deep Learning with Mixed Supervision for Brain Tumor Segmentation

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

December 2018

Publication Project

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 Project

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 Project

Quantifying Registration Uncertainty with Sparse Bayesian Modeling

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

IEEE Transactions on Medical Imaging | December 2016

Publication Project

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 Project Project

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 Project Project

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 Project Project

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 Project

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 Project Project

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 Project

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 Project

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 Project

RAD-DINO: 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

MSR-TR-2024-5 | January 2024

Published by Microsoft

Preprint Project

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 Project

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 Download Project

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 Project Project

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 Video Download Download Project

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 Project Project

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 Project Project

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 Project Project

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 Project

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 Project

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 Project Project Project Project

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 Project

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 Project

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 Project Project

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 Video Github Project

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 Project

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 Project

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 Project

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 Project

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 Project

Deep Learning with Mixed Supervision for Brain Tumor Segmentation

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

December 2018

Publication Project

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 Project

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 Project

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 Project

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 Project

Constrained Deep Weak Supervision for Histopathology Image Segmentation

Zhipeng Jia, Xingyi Huang, Eric Chang, Yan Xu

IEEE Transactions on Medical Imaging | November 2017

Publication Project

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 Project

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 Project

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 Project

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 Project

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 Project

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 Project

Quantifying Registration Uncertainty with Sparse Bayesian Modeling

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

IEEE Transactions on Medical Imaging | December 2016

Publication Project

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 Project

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 Project

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 Project

Gland Instance Segmentation by Deep Multichannel Side Supervision

Eric Chang

January 2016

Publication Project

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

Eric Chang

January 2015

Publication Project

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 Project

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

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 Project Project

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 Project

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 Project

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 Project Project

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 Project Project

RAD-DINO: 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

MSR-TR-2024-5 | January 2024

Published by Microsoft

Preprint Project

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

Published by Microsoft

Publication Project

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 Project

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 Project

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 Download Project

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

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 Video Download Download Project

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 Project Project Project Project

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 Project

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 Project Project

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 Project

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 Project

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 Project

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 Project

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 Project

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 Project

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 Project

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 Project

Gland Instance Segmentation by Deep Multichannel Side Supervision

Eric Chang

January 2016

Publication Project

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 Project

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 Project Project

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

Eric Chang

January 2015

Publication Project

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 Project Project

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 Project Project

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 Project Project

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 Project Project

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 Project

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 Project

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 Project

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 Video Github Project

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 Project

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 Project

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 Project

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 Project

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 Project

Constrained Deep Weak Supervision for Histopathology Image Segmentation

Zhipeng Jia, Xingyi Huang, Eric Chang, Yan Xu

IEEE Transactions on Medical Imaging | November 2017

Publication Project

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 Project

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 Project

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 Project

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 Project

Quantifying Registration Uncertainty with Sparse Bayesian Modeling

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

IEEE Transactions on Medical Imaging | December 2016

Publication Project

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 Project Project

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 Project

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 Project

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 Project

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 Project

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 Project

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 Project

Deep Learning with Mixed Supervision for Brain Tumor Segmentation

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

December 2018

Publication Project

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 Project Project

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 Project Project