Semi-automatic Liver Tumor Segmentation in Dynamic Contrast-Enhanced CT Scans Using Random Forests and Supervoxels. - Pierre-Henri Conze; François Rousseau 002; Vincent Noblet; Fabrice Heitz; Riccardo Memeo; Patrick Pessaux (MLMI, 2015)

Random forests on hierarchical multi-scale supervoxels for liver tumor segmentation in dynamic contrast-enhanced CT scans. - Pierre-Henri Conze; Vincent Noblet; François Rousseau 002; Fabrice Heitz; Riccardo Memeo; Patrick Pessaux (ISBI, 2016)

Hierarchical multi-scale supervoxel matching using random forests for automatic semi-dense abdominal image registration. - Pierre-Henri Conze; Florian Tilquin; Vincent Noblet; François Rousseau 002; Fabrice Heitz; Patrick Pessaux (ISBI, 2017)

Scale-adaptive supervoxel-based random forests for liver tumor segmentation in dynamic contrast-enhanced CT scans. - Pierre-Henri Conze; Vincent Noblet; François Rousseau 002; Fabrice Heitz; Vito de Blasi; Riccardo Memeo; Patrick Pessaux (Int. J. Comput. Assist. Radiol. Surg., 2017)

Robust Supervoxel Matching Combining Mid-Level Spectral and Context-Rich Features. - Florian Tilquin; Pierre-Henri Conze; Patrick Pessaux; Mathieu Lamard; Gwenolé Quellec; Vincent Noblet; Fabrice Heitz (Patch-MI@MICCAI, 2018)

Liver tissue segmentation in multiphase CT scans using cascaded convolutional neural networks. - Farid Ouhmich; Vincent Agnus; Vincent Noblet; Fabrice Heitz; Patrick Pessaux (Int. J. Comput. Assist. Radiol. Surg., 2019)

A human liver cell atlas reveals heterogeneity and epithelial progenitors. - Nadim Aizarani; Antonio Saviano; Sagar; Laurent Mailly; Sarah Durand; Josip S. Herman; Patrick Pessaux; Thomas F. Baumert; Dominic Grün (Nat., 2019)