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Matthew C. H. Lee
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2020 – today
- 2024
- [i14]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:
Screen Them All: High-Throughput Pan-Cancer Genetic and Phenotypic Biomarker Screening from H&E Whole Slide Images. CoRR abs/2408.09554 (2024) - 2023
- [i13]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:
Virchow: A Million-Slide Digital Pathology Foundation Model. CoRR abs/2309.07778 (2023) - 2020
- [c9]Katarína Tóthová, Sarah Parisot, Matthew C. H. Lee, Esther Puyol-Antón, Andrew P. King, Marc Pollefeys, Ender Konukoglu:
Probabilistic 3D Surface Reconstruction from Sparse MRI Information. MICCAI (1) 2020: 813-823 - [i12]Katarína Tóthová, Sarah Parisot, Matthew C. H. Lee, Esther Puyol-Antón, Andrew P. King, Marc Pollefeys, Ender Konukoglu:
Probabilistic 3D surface reconstruction from sparse MRI information. CoRR abs/2010.02041 (2020)
2010 – 2019
- 2019
- [j4]Matthew C. H. Lee, Kersten Petersen, Nick Pawlowski, Ben Glocker, Michiel Schaap:
TeTrIS: Template Transformer Networks for Image Segmentation With Shape Priors. IEEE Trans. Medical Imaging 38(11): 2596-2606 (2019) - [c8]Matthew C. H. Lee, Ozan Oktay, Andreas Schuh, Michiel Schaap, Ben Glocker:
Image-and-Spatial Transformer Networks for Structure-Guided Image Registration. MICCAI (2) 2019: 337-345 - [i11]Matthew C. H. Lee, Ozan Oktay, Andreas Schuh, Michiel Schaap, Ben Glocker:
Image-and-Spatial Transformer Networks for Structure-Guided Image Registration. CoRR abs/1907.09200 (2019) - 2018
- [j3]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero, Ben Glocker, Daniel Rueckert:
Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease. Medical Image Anal. 48: 117-130 (2018) - [j2]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Metric learning with spectral graph convolutions on brain connectivity networks. NeuroImage 169: 431-442 (2018) - [c7]Katarína Tóthová, Sarah Parisot, Matthew C. H. Lee, Esther Puyol-Antón, Lisa M. Koch, Andrew P. King, Ender Konukoglu, Marc Pollefeys:
Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors. ShapeMI@MICCAI 2018: 300-310 - [c6]Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C. H. Lee, Amir Alansary, Steven G. McDonagh, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry. MICCAI (1) 2018: 756-764 - [i10]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:
Attention U-Net: Learning Where to Look for the Pancreas. CoRR abs/1804.03999 (2018) - [i9]Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C. H. Lee, Amir Alansary, Steven G. McDonagh, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry. CoRR abs/1805.01026 (2018) - [i8]Katarína Tóthová, Sarah Parisot, Matthew C. H. Lee, Esther Puyol-Antón, Lisa M. Koch, Andrew P. King, Ender Konukoglu, Marc Pollefeys:
Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors. CoRR abs/1807.11272 (2018) - 2017
- [j1]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:
DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks. IEEE Trans. Medical Imaging 36(2): 674-683 (2017) - [c5]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert:
Spectral Graph Convolutions for Population-Based Disease Prediction. MICCAI (3) 2017: 177-185 - [c4]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:
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation. BrainLes@MICCAI 2017: 450-462 - [c3]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Distance Metric Learning Using Graph Convolutional Networks: Application to Functional Brain Networks. MICCAI (1) 2017: 469-477 - [i7]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks. CoRR abs/1703.02161 (2017) - [i6]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert:
Spectral Graph Convolutions for Population-based Disease Prediction. CoRR abs/1703.03020 (2017) - [i5]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:
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation. CoRR abs/1711.01468 (2017) - [i4]Nick Pawlowski, Sofia Ira Ktena, Matthew C. H. Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker, Martin Rajchl:
DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images. CoRR abs/1711.06853 (2017) - 2016
- [c2]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:
Multi-input Cardiac Image Super-Resolution Using Convolutional Neural Networks. MICCAI (3) 2016: 246-254 - [i3]Martin Rajchl, Matthew C. H. Lee, Ozan Oktay, Konstantinos Kamnitsas, Jonathan Passerat-Palmbach, Wenjia Bai, Bernhard Kainz, Daniel Rueckert:
DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks. CoRR abs/1605.07866 (2016) - [i2]Martin Rajchl, Matthew C. H. Lee, Franklin Schrans, Alice Davidson, Jonathan Passerat-Palmbach, Giacomo Tarroni, Amir Alansary, Ozan Oktay, Bernhard Kainz, Daniel Rueckert:
Learning under Distributed Weak Supervision. CoRR abs/1606.01100 (2016) - [i1]Nat Dilokthanakul, Pedro A. M. Mediano, Marta Garnelo, Matthew C. H. Lee, Hugh Salimbeni, Kai Arulkumaran, Murray Shanahan:
Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders. CoRR abs/1611.02648 (2016) - 2015
- [c1]Amir Alansary, Matthew C. H. Lee, Kevin Keraudren, Bernhard Kainz, Christina Malamateniou, Mary A. Rutherford, Joseph V. Hajnal, Ben Glocker, Daniel Rueckert:
Automatic Brain Localization in Fetal MRI Using Superpixel Graphs. MLMMI@ICML 2015: 13-22
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