Normalisation of Neonatal Brain Network Measures Using Stochastic Approaches. - Markus Schirmer; Gareth Ball; Serena J. Counsell; A. David Edwards; Daniel Rueckert; Joseph V. Hajnal; Paul Aljabar (MICCAI (1), 2013)

GraMPa: Graph-Based Multi-modal Parcellation of the Cortex Using Fusion Moves. - Sarah Parisot; Ben Glocker; Markus Schirmer; Daniel Rueckert (MICCAI (1), 2016)

Proceedings of the Workshop on Brain Analysis using COnnectivity Networks - BACON 2016. - Sarah Parisot; Jonathan Passerat-Palmbach; Markus D. Schirmer; Boris Gutman (CoRR, 2016)

Characterising brain network topologies: A dynamic analysis approach using heat kernels. - Ai Wern Chung; Markus Schirmer; Michelle L. Krishnan; Gareth Ball; Paul Aljabar; A. David Edwards; Giovanni Montana (NeuroImage, 2016)

A flexible graphical model for multi-modal parcellation of the cortex. - Sarah Parisot; Ben Glocker; Sofia Ira Ktena; Salim Arslan; Markus D. Schirmer; Daniel Rueckert (NeuroImage, 2017)

Structural Subnetwork Evolution Across the Life-Span: Rich-Club, Feeder, Seeder. - Markus D. Schirmer; Ai Wern Chung (CNI@MICCAI, 2018)

Network Dependency Index Stratified Subnetwork Analysis of Functional Connectomes: An Application to Autism. - Ai Wern Chung; Markus D. Schirmer (CNI@MICCAI, 2019)

Patient-Specific Conditional Joint Models of Shape, Image Features and Clinical Indicators. - Bernhard Egger; Markus D. Schirmer; Florian Dubost; Marco J. Nardin; Natalia S. Rost; Polina Golland (MICCAI (4), 2019)

Heat Kernels with Functional Connectomes Reveal Atypical Energy Transport in Peripheral Subnetworks in Autism. - Markus D. Schirmer; Ai Wern Chung (CNI@MICCAI, 2019)

Automated Image Registration Quality Assessment Utilizing Deep-learning based Ventricle Extraction in Clinical Data. - Florian Dubost; Marleen de Bruijne; Marco Nardin; Adrian V. Dalca; Kathleen L. Donahue; Anne-Katrin Giese; Mark R. Etherton; Ona Wu; Marius de Groot; Wiro J. Niessen; Meike W. Vernooij; Natalia S. Rost; et al. (CoRR, 2019)

Neuropsychiatric Disease Classification Using Functional Connectomics - Results of the Connectomics in NeuroImaging Transfer Learning Challenge. - Markus D. Schirmer; Archana Venkataraman; Islem Rekik; Minjeong Kim; Stewart Mostofsky; Mary Beth Nebel; Keri Rosch; Karen Seymour; Deana Crocetti; Hassna Irzan; Michael Hütel; Sébastien Ourselin; et al. (CoRR, 2020)

Multi-atlas image registration of clinical data with automated quality assessment using ventricle segmentation. - Florian Dubost; Marleen de Bruijne; Marco Nardin; Adrian V. Dalca; Kathleen L. Donahue; Anne-Katrin Giese; Mark R. Etherton; Ona Wu; Marius de Groot; Wiro J. Niessen; Meike W. Vernooij; Natalia S. Rost; et al. (Medical Image Anal., 2020)

Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels. - Sungmin Hong; Anna K. Bonkhoff; Andrew Hoopes; Martin Bretzner; Markus D. Schirmer; Anne-Katrin Giese; Adrian V. Dalca; Polina Golland; Natalia S. Rost (CoRR, 2021)

Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroimaging transfer learning challenge. - Markus D. Schirmer; Archana Venkataraman; Islem Rekik; Minjeong Kim; Stewart H. Mostofsky; Mary Beth Nebel; Keri Rosch; Karen Seymour; Deana Crocetti; Hassna Irzan; Michael Hütel; Sébastien Ourselin; et al. (Medical Image Anal., 2021)

Federated Learning for MRI-based BrainAGE: a multicenter study on post-stroke functional outcome prediction. - Vincent Roca; Marc Tommasi; Paul Andrey; Aurélien Bellet; Markus D. Schirmer; Hilde Henon; Laurent Puy; Julien Ramon; Grégory Kuchcinski; Martin Bretzner; Renaud Lopes (CoRR, 2025)