Multi-class brain segmentation using atlas propagation and EM-based refinement. - Christian Ledig; Robin Wolz; Paul Aljabar; Jyrki Lötjönen; Rolf A. Heckemann; Alexander Hammers; Daniel Rueckert (ISBI, 2012)

Hippocampal atrophy rate using an expectation maximization classifier with a disease-specific prior. - Jyrki Lötjönen; Robin Wolz; Juha Koikkalainen; Valeria Manna; Christian Ledig; Lennart Thurfjell; Roger Lundqvist; Gunhild Waldemar; Hilkka Soininen; Daniel Rueckert (ISBI, 2012)

Cardiac Image Super-Resolution with Global Correspondence Using Multi-Atlas PatchMatch. - Wenzhe Shi; Jose Caballero; Christian Ledig; Xiahai Zhuang; Wenjia Bai; Kanwal K. Bhatia; Antonio M. Simoes Monteiro de Marvao; Tim Dawes; Declan P. O'Regan; Daniel Rueckert (MICCAI (3), 2013)

Improving whole-brain segmentations through incorporating regional image intensity statistics. - Christian Ledig; Rolf A. Heckemann; Alexander Hammers; Daniel Rueckert (Image Processing, 2013)

A Framework for Inter-Subject Prediction of Functional Connectivity From Structural Networks. - Fani Deligianni; Gaël Varoquaux; Bertrand Thirion; David J. Sharp; Christian Ledig; Robert Leech; Daniel Rueckert (IEEE Trans. Medical Imaging, 2013)

Patch-Based Evaluation of Image Segmentation. - Christian Ledig; Wenzhe Shi; Wenjia Bai; Daniel Rueckert (CVPR, 2014)

Automatic quantification of CT images for traumatic brain injury. - Juha Koikkalainen; Jyrki Lötjönen; Christian Ledig; Daniel Rueckert; Olli Tenovuo; David K. Menon (ISBI, 2014)

Consistent and robust 4D whole-brain segmentation: Application to traumatic brain injury. - Christian Ledig; Wenzhe Shi; Antonios Makropoulos; Juha Koikkalainen; Rolf A. Heckemann; Alexander Hammers; Jyrki Lötjönen; Olli Tenovuo; Daniel Rueckert (ISBI, 2014)

Extended boundary shift integral. - Jyrki Lötjönen; Christian Ledig; Juha Koikkalainen; Robin Wolz; Lennart Thurfjell; Hilkka Soininen; Sébastien Ourselin; Daniel Rueckert (ISBI, 2014)

A robust similarity measure for nonrigid image registration with outliers. - Stefan Pszczólkowski; Stefanos Zafeiriou; Christian Ledig; Daniel Rueckert (ISBI, 2014)

Contusion segmentation from subjects with Traumatic Brain Injury: A random forest framework. - Anil Rao; Christian Ledig; Virginia F. J. Newcombe; David K. Menon; Daniel Rueckert (ISBI, 2014)

Manifold Alignment and Transfer Learning for Classification of Alzheimer's Disease. - Ricardo Guerrero; Christian Ledig; Daniel Rueckert (MLMI, 2014)

Construction of a 4D Brain Atlas and Growth Model Using Diffeomorphic Registration. - Andreas Schuh; Maria Murgasova; Antonios Makropoulos; Christian Ledig; Serena J. Counsell; Joseph V. Hajnal; Paul Aljabar; Daniel Rueckert (STIA, 2014)

Multi-atlas Spectral PatchMatch: Application to Cardiac Image Segmentation. - Wenzhe Shi; Herve Lombaert; Wenjia Bai; Christian Ledig; Xiahai Zhuang; Antonio M. Simoes Monteiro de Marvao; Timothy Dawes; Declan P. O'Regan; Daniel Rueckert (MICCAI (1), 2014)

Automatic quantification of normal cortical folding patterns from fetal brain MRI. - Robert Wright; Vanessa Kyriakopoulou; Christian Ledig; Mary A. Rutherford; Joseph V. Hajnal; Daniel Rueckert; Paul Aljabar (NeuroImage, 2014)

Automatic Whole Brain MRI Segmentation of the Developing Neonatal Brain. - Antonios Makropoulos; Ioannis S. Gousias; Christian Ledig; Paul Aljabar; Ahmed Serag; Joseph V. Hajnal; A. David Edwards; Serena J. Counsell; Daniel Rueckert (IEEE Trans. Medical Imaging, 2014)

Multi-stage Biomarker Models for Progression Estimation in Alzheimer's Disease. - Alexander Schmidt-Richberg; Ricardo Guerrero; Christian Ledig; Helena Molina-Abril; Alejandro F. Frangi; Daniel Rueckert (IPMI, 2015)

Group-Constrained Laplacian Eigenmaps: Longitudinal AD Biomarker Learning. - Ricardo Guerrero; Christian Ledig; Alexander Schmidt-Richberg; Daniel Rueckert (MLMI, 2015)

Multi-atlas segmentation with augmented features for cardiac MR images. - Wenjia Bai; Wenzhe Shi; Christian Ledig; Daniel Rueckert (Medical Image Anal., 2015)

Robust whole-brain segmentation: Application to traumatic brain injury. - Christian Ledig; Rolf A. Heckemann; Alexander Hammers; Juan Carlos López; Virginia F. J. Newcombe; Antonios Makropoulos; Jyrki Lötjönen; David K. Menon; Daniel Rueckert (Medical Image Anal., 2015)

Robust multi-structure segmentation of magnetic resonance brain images. - Christian Ledig (2015)

Regression analysis for assessment of myelination status in preterm brains with magnetic resonance imaging. - Siying Wang 004; Maria Kuklisova-Murgasova; Joseph V. Hajnal; Christian Ledig; Julia A. Schnabel (ISBI, 2016)

Pseudo-healthy Image Synthesis for White Matter Lesion Segmentation. - Christopher Bowles; Chen Qin; Christian Ledig; Ricardo Guerrero; Roger N. Gunn; Alexander Hammers; Eleni Sakka; David Alexander Dickie; Maria del C. Valdés Hernández; Natalie A. Royle; Joanna M. Wardlaw; Hanneke Rhodius-Meester; et al. (SASHIMI@MICCAI, 2016)

DeepMedic for Brain Tumor Segmentation. - Konstantinos Kamnitsas; Enzo Ferrante; Sarah Parisot; Christian Ledig; Aditya V. Nori; Antonio Criminisi; Daniel Rueckert; Ben Glocker (BrainLes@MICCAI, 2016)

Differential Dementia Diagnosis on Incomplete Data with Latent Trees. - Christian Ledig; Sebastian Kaltwang; Antti Tolonen; Juha Koikkalainen; Philip Scheltens; Frederik Barkhof; Hanneke Rhodius-Meester; Betty M. Tijms; Afina W. Lemstra; Wiesje M. van der Flier; Jyrki Lötjönen; Daniel Rueckert (MICCAI (2), 2016)

A Semi-supervised Large Margin Algorithm for White Matter Hyperintensity Segmentation. - Chen Qin; Ricardo Guerrero Moreno; Christopher Bowles; Christian Ledig; Philip Scheltens; Frederik Barkhof; Hanneke Rhodius-Meester; Betty M. Tijms; Afina W. Lemstra; Wiesje M. van der Flier; Ben Glocker; Daniel Rueckert (MLMI@MICCAI, 2016)

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. - Christian Ledig; Lucas Theis; Ferenc Huszar; Jose Caballero; Andrew P. Aitken; Alykhan Tejani; Johannes Totz; Zehan Wang; Wenzhe Shi (CoRR, 2016)

Is the deconvolution layer the same as a convolutional layer? - Wenzhe Shi; Jose Caballero; Lucas Theis; Ferenc Huszar; Andrew P. Aitken; Christian Ledig; Zehan Wang (CoRR, 2016)

A robust similarity measure for volumetric image registration with outliers. - Patrick Snape; Stefan Pszczólkowski; Stefanos Zafeiriou; Georgios Tzimiropoulos; Christian Ledig; Daniel Rueckert (Image Vis. Comput., 2016)

Instantiated mixed effects modeling of Alzheimer's disease markers. - Ricardo Guerrero; Alexander Schmidt-Richberg; Christian Ledig; Tong Tong 001; Robin Wolz; Daniel Rueckert (NeuroImage, 2016)

Real-Time Video Super-Resolution with Spatio-Temporal Networks and Motion Compensation. - Jose Caballero; Christian Ledig; Andrew P. Aitken; Alejandro Acosta; Johannes Totz; Zehan Wang; Wenzhe Shi (CVPR, 2017)

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. - Christian Ledig; Lucas Theis; Ferenc Huszar; Jose Caballero; Andrew Cunningham; Alejandro Acosta; Andrew P. Aitken; Alykhan Tejani; Johannes Totz; Zehan Wang; Wenzhe Shi (CVPR, 2017)

Unsupervised Domain Adaptation in Brain Lesion Segmentation with Adversarial Networks. - Konstantinos Kamnitsas; Christian F. Baumgartner; Christian Ledig; Virginia F. J. Newcombe; Joanna P. Simpson; Andrew D. Kane; David K. Menon; Aditya V. Nori; Antonio Criminisi; Daniel Rueckert; Ben Glocker (IPMI, 2017)

Checkerboard artifact free sub-pixel convolution: A note on sub-pixel convolution, resize convolution and convolution resize. - Andrew P. Aitken; Christian Ledig; Lucas Theis; Jose Caballero; Zehan Wang; Wenzhe Shi (CoRR, 2017)

Employing Weak Annotations for Medical Image Analysis Problems. - Martin Rajchl; Lisa M. Koch; Christian Ledig; Jonathan Passerat-Palmbach; Kazunari Misawa; Kensaku Mori; Daniel Rueckert (CoRR, 2017)

Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation. - Konstantinos Kamnitsas; Christian Ledig; Virginia F. J. Newcombe; Joanna P. Simpson; Andrew D. Kane; David K. Menon; Daniel Rueckert; Ben Glocker (Medical Image Anal., 2017)

Group-constrained manifold learning: Application to AD risk assessment. - Ricardo Guerrero; Christian Ledig; Alexander Schmidt-Richberg; Daniel Rueckert (Pattern Recognit., 2017)

A Novel Grading Biomarker for the Prediction of Conversion From Mild Cognitive Impairment to Alzheimer's Disease. - Tong Tong 001; Qinquan Gao; Ricardo Guerrero; Christian Ledig; Liang Chen 018; Daniel Rueckert (IEEE Trans. Biomed. Eng., 2017)

Generative adversarial networks and adversarial methods in biomedical image analysis. - Jelmer M. Wolterink; Konstantinos Kamnitsas; Christian Ledig; Ivana Isgum (CoRR, 2018)

Generative Image Translation for Data Augmentation of Bone Lesion Pathology. - Anant Gupta; Srivas Venkatesh; Sumit Chopra; Christian Ledig (MIDL, 2019)

Assessment of a deep-learning system for fracture detection in musculoskeletal radiographs. - Rebecca M. Jones; Anuj Sharma; Robert Hotchkiss; John W. Sperling; Jackson Hamburger; Christian Ledig; Robert O'Toole; Michael Gardner; Srivas Venkatesh; Matthew M. Roberts; Romain Sauvestre; Max Shatkhin; et al. (npj Digit. Medicine, 2020)

Explainable Anatomical Shape Analysis Through Deep Hierarchical Generative Models. - Carlo Biffi; Juan J. Cerrolaza; Giacomo Tarroni; Wenjia Bai; Antonio de Marvao; Ozan Oktay; Christian Ledig; Loïc Le Folgoc; Konstantinos Kamnitsas; Georgia Doumou; Jinming Duan 001; Sanjay K. Prasad; et al. (IEEE Trans. Medical Imaging, 2020)

Differences Between MR Brain Region Segmentation Methods: Impact on Single-Subject Analysis. - Wyke Huizinga; Dirk H. J. Poot; Elisabeth J. Vinke; F. Wenzel; Esther Bron; N. Toussaint; Christian Ledig; Henri A. Vrooman; Mohammad Arfan Ikram; Wiro J. Niessen; Meike W. Vernooij; Stefan Klein 001 (Frontiers Big Data, 2021)

unORANIC: Unsupervised Orthogonalization of Anatomy and Image-Characteristic Features. - Sebastian Doerrich; Francesco Di Salvo; Christian Ledig (MLMI@MICCAI (1), 2023)

Unsupervised Feature Orthogonalization for Learning Distortion-Invariant Representations. - Sebastian Doerrich; Francesco Di Salvo; Christian Ledig (BMVC Workshops, 2024)

Privacy-preserving datasets by capturing feature distributions with Conditional VAEs. - Francesco Di Salvo; David Tafler; Sebastian Doerrich; Christian Ledig (BMVC, 2024)

Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image Classification. - Sebastian Doerrich; Tobias Archut; Francesco Di Salvo; Christian Ledig (ISBI, 2024)

Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization. - Sebastian Doerrich; Francesco Di Salvo; Christian Ledig (MICCAI (10), 2024)

Rethinking Model Prototyping through the MedMNIST+ Dataset Collection. - Sebastian Doerrich; Francesco Di Salvo; Julius Brockmann; Christian Ledig (CoRR, 2024)

MedMNIST-C: Comprehensive benchmark and improved classifier robustness by simulating realistic image corruptions. - Francesco Di Salvo; Sebastian Doerrich; Christian Ledig (CoRR, 2024)

An Embedding is Worth a Thousand Noisy Labels. - Francesco Di Salvo; Sebastian Doerrich; Ines Rieger; Christian Ledig (Trans. Mach. Learn. Res., 2025)

Embedding-Based Federated Data Sharing via Differentially Private Conditional VAEs. - Francesco Di Salvo; Hanh Huyen My Nguyen; Christian Ledig (CoRR, 2025)