Matthew C. H. Lee

According to our database, Matthew C. H. Lee authored at least 20 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Screen Them All: High-Throughput Pan-Cancer Genetic and Phenotypic Biomarker Screening from H&E Whole Slide Images.

Yi Kan Wang, Ludmila Tydlitatova, Jeremy D. Kunz, Gerard Oakley, Ran A. Godrich, Matthew C. H. Lee, Chad Vanderbilt, Razik Yousfi, Thomas Fuchs, David S. Klimstra, Siqi Liu

CoRR, 2024

2023

Virchow: A Million-Slide Digital Pathology Foundation Model.

Eugene Vorontsov, Alican Bozkurt, Adam Casson, George Shaikovski, Michal Zelechowski, Siqi Liu, Philippe Mathieu, Alexander van Eck, Donghun Lee, Julian Viret, Eric Robert, Yi Kan Wang, Jeremy D. Kunz, Matthew C. H. Lee, Jan Bernhard, Ran A. Godrich, Gerard Oakley, Ewan Millar, Matthew G. Hanna, Juan Retamero, William A. Moye, Razik Yousfi, Christopher Kanan, David S. Klimstra, Brandon Rothrock, Thomas J. Fuchs

CoRR, 2023

2020

Probabilistic 3D Surface Reconstruction from Sparse MRI Information.

Katarína Tóthová, Sarah Parisot, Matthew C. H. Lee, Esther Puyol-Antón, Andrew P. King, Marc Pollefeys, Ender Konukoglu

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

2019

TeTrIS: Template Transformer Networks for Image Segmentation With Shape Priors.

Matthew C. H. Lee, Kersten Petersen, Nick Pawlowski, Ben Glocker, Michiel Schaap

IEEE Trans. Medical Imaging, 2019

Image-and-Spatial Transformer Networks for Structure-Guided Image Registration.

Matthew C. H. Lee, Ozan Oktay, Andreas Schuh, Michiel Schaap, Ben Glocker

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

2018

Metric learning with spectral graph convolutions on brain connectivity networks.

Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert

NeuroImage, 2018

Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease.

Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero, Ben Glocker, Daniel Rueckert

Medical Image Anal., 2018

Attention U-Net: Learning Where to Look for the Pancreas.

Ozan Oktay, Jo Schlemper, Loïc Le Folgoc, Matthew C. H. Lee, Mattias P. Heinrich, Kazunari Misawa, Kensaku Mori, Steven G. McDonagh, Nils Y. Hammerla, Bernhard Kainz, Ben Glocker, Daniel Rueckert

CoRR, 2018

Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors.

Katarína Tóthová, Sarah Parisot, Matthew C. H. Lee, Esther Puyol-Antón, Lisa M. Koch, Andrew P. King, Ender Konukoglu, Marc Pollefeys

Proceedings of the Shape in Medical Imaging, 2018

Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry.

Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C. H. Lee, Amir Alansary, Steven G. McDonagh, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

2017

DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks.

Martin Rajchl, Matthew C. H. Lee, Ozan Oktay, Konstantinos Kamnitsas, Jonathan Passerat-Palmbach, Wenjia Bai, Mellisa Damodaram, Mary A. Rutherford, Joseph V. Hajnal, Bernhard Kainz, Daniel Rueckert

IEEE Trans. Medical Imaging, 2017

DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images.

Nick Pawlowski, Sofia Ira Ktena, Matthew C. H. Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker, Martin Rajchl

CoRR, 2017

Spectral Graph Convolutions for Population-Based Disease Prediction.

Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Distance Metric Learning Using Graph Convolutional Networks: Application to Functional Brain Networks.

Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation.

Konstantinos Kamnitsas, Wenjia Bai, Enzo Ferrante, Steven G. McDonagh, Matthew Sinclair, Nick Pawlowski, Martin Rajchl, Matthew C. H. Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017

2016

Learning under Distributed Weak Supervision.

Martin Rajchl, Matthew C. H. Lee, Franklin Schrans, Alice Davidson, Jonathan Passerat-Palmbach, Giacomo Tarroni, Amir Alansary, Ozan Oktay, Bernhard Kainz, Daniel Rueckert

CoRR, 2016

DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks.

Martin Rajchl, Matthew C. H. Lee, Ozan Oktay, Konstantinos Kamnitsas, Jonathan Passerat-Palmbach, Wenjia Bai, Bernhard Kainz, Daniel Rueckert

CoRR, 2016

Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders.

Nat Dilokthanakul, Pedro A. M. Mediano, Marta Garnelo, Matthew C. H. Lee, Hugh Salimbeni, Kai Arulkumaran, Murray Shanahan

CoRR, 2016

Multi-input Cardiac Image Super-Resolution Using Convolutional Neural Networks.

Ozan Oktay, Wenjia Bai, Matthew C. H. Lee, Ricardo Guerrero, Konstantinos Kamnitsas, Jose Caballero, Antonio de Marvao, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

2015

Automatic Brain Localization in Fetal MRI Using Superpixel Graphs.

Amir Alansary, Matthew C. H. Lee, Kevin Keraudren, Bernhard Kainz, Christina Malamateniou, Mary A. Rutherford, Joseph V. Hajnal, Ben Glocker, Daniel Rueckert

Proceedings of the Machine Learning Meets Medical Imaging - First International Workshop, 2015