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Weakly Supervised Estimation of Shadow Confidence Maps in Ultrasound Imaging


Nov 21, 2018
Qingjie Meng, Matthew Sinclair, Veronika Zimmer, Benjamin Hou, Martin Rajchl, Nicolas Toussaint, Alberto Gomez, James Housden, Jacqueline Matthew, Daniel Rueckert, Julia Schnabel, Bernhard Kainz


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Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling


Jul 18, 2018
Carlo Biffi, Ozan Oktay, Giacomo Tarroni, Wenjia Bai, Antonio De Marvao, Georgia Doumou, Martin Rajchl, Reem Bedair, Sanjay Prasad, Stuart Cook, Declan O'Regan, Daniel Rueckert

* Accepted at MICCAI 2018 

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Deep Generative Models in the Real-World: An Open Challenge from Medical Imaging


Jun 14, 2018
Xiaoran Chen, Nick Pawlowski, Martin Rajchl, Ben Glocker, Ender Konukoglu

* 10 pages. 3 figures 

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NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines


Jun 11, 2018
Martin Rajchl, Nick Pawlowski, Daniel Rueckert, Paul M. Matthews, Ben Glocker

* International conference on Medical Imaging with Deep Learning (MIDL) 2018 

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Implicit Weight Uncertainty in Neural Networks


May 25, 2018
Nick Pawlowski, Andrew Brock, Matthew C. H. Lee, Martin Rajchl, Ben Glocker

* Submitted to NIPS 2018, under review 

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Automated cardiovascular magnetic resonance image analysis with fully convolutional networks


May 22, 2018
Wenjia Bai, Matthew Sinclair, Giacomo Tarroni, Ozan Oktay, Martin Rajchl, Ghislain Vaillant, Aaron M. Lee, Nay Aung, Elena Lukaschuk, Mihir M. Sanghvi, Filip Zemrak, Kenneth Fung, Jose Miguel Paiva, Valentina Carapella, Young Jin Kim, Hideaki Suzuki, Bernhard Kainz, Paul M. Matthews, Steffen E. Petersen, Stefan K. Piechnik, Stefan Neubauer, Ben Glocker, Daniel Rueckert

* Accepted for publication by Journal of Cardiovascular Magnetic Resonance 

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


Nov 18, 2017
Nick Pawlowski, Sofia Ira Ktena, Matthew C. H. Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker, Martin Rajchl

* Submitted to Medical Imaging Meets NIPS 2017, Code at https://github.com/DLTK/DLTK 

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Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation


Nov 04, 2017
Konstantinos Kamnitsas, Wenjia Bai, Enzo Ferrante, Steven McDonagh, Matthew Sinclair, Nick Pawlowski, Martin Rajchl, Matthew Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker

* The method won the 1st-place in the Brain Tumour Segmentation (BRATS) 2017 competition (segmentation task) 

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Employing Weak Annotations for Medical Image Analysis Problems


Aug 21, 2017
Martin Rajchl, Lisa M. Koch, Christian Ledig, Jonathan Passerat-Palmbach, Kazunari Misawa, Kensaku Mori, Daniel Rueckert


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Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks


Jun 14, 2017
Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew Lee, Ben Glocker, Daniel Rueckert

* International Conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI) 2017 

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PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI


Nov 25, 2016
Amir Alansary, Bernhard Kainz, Martin Rajchl, Maria Murgasova, Mellisa Damodaram, David F. A. Lloyd, Alice Davidson, Steven G. McDonagh, Mary Rutherford, Joseph V. Hajnal, Daniel Rueckert

* 10 pages, 13 figures, submitted to IEEE Transactions on Medical Imaging. v2: wadded funders acknowledgements to preprint 

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


Jun 05, 2016
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


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Learning under Distributed Weak Supervision


Jun 03, 2016
Martin Rajchl, Matthew C. H. Lee, Franklin Schrans, Alice Davidson, Jonathan Passerat-Palmbach, Giacomo Tarroni, Amir Alansary, Ozan Oktay, Bernhard Kainz, Daniel Rueckert


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Multi-Atlas Segmentation using Partially Annotated Data: Methods and Annotation Strategies


Apr 29, 2016
Lisa M. Koch, Martin Rajchl, Wenjia Bai, Christian F. Baumgartner, Tong Tong, Jonathan Passerat-Palmbach, Paul Aljabar, Daniel Rueckert


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A Proximal Bregman Projection Approach to Continuous Max-Flow Problems Using Entropic Distances


Jan 30, 2015
John S. H. Baxter, Martin Rajchl, Jing Yuan, Terry M. Peters

* 10 pages 

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A Continuous Max-Flow Approach to Multi-Labeling Problems under Arbitrary Region Regularization


Jun 05, 2014
John S. H. Baxter, Martin Rajchl, Jing Yuan, Terry M. Peters

* 10 pages, 2 figures, 3 algorithms - v2: Fixed typos / grammatical errors and mathematical errors in the primal/dual formulation. Extended methods for weighted DAGs rather than DAGs with edge multiplicity 

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A Continuous Max-Flow Approach to General Hierarchical Multi-Labeling Problems


Jun 05, 2014
John S. H. Baxter, Martin Rajchl, Jing Yuan, Terry M. Peters

* 11 pages, 1 figure, 3 algorithms -v2: Fixed typos / grammatical errors 

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RANCOR: Non-Linear Image Registration with Total Variation Regularization


Apr 09, 2014
Martin Rajchl, John S. H. Baxter, Wu Qiu, Ali R. Khan, Aaron Fenster, Terry M. Peters, Jing Yuan

* 9 pages, 1 figure, technical note 

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