Statistical shape models (SSMs) have by now been firmly established as a robust tool for
segmentation of medical images. While 2D models have been in use since the early 1990s …

Anatomical segmentation is a fundamental task in medical image computing, generally
tackled with fully convolutional neural networks which produce dense segmentation masks …

In this work we address the problem of landmark-based segmentation for anatomical
structures. We propose HybridGNet, an encoder-decoder neural architecture which …

Active shape models (ASMs) have been studied extensively for the statistical analysis of
three-dimensional shapes. These models can be used as prior information for segmentation …

Methods and an apparatus process images. The method according to one embodiment
accesses digital image data representing a plurality of objects with a plurality of features; …

The 9th International Conference on Medical Image Computing and Computer Assisted
Intervention, MICCAI 2006, was held in Copenhagen, Denmark at the Tivoli Concert Hall …

Abstract Two-dimensional (2D) radiographs are widely used for diagnosis, treatment
planning, and follow-up in orthopedics. The images depict bone at high contrast to …

Computer-aided detection (CAD) has become increasingly common in recent years as a tool
in catching breast cancer in its early, more treatable stages. More and more breast centers …

Résumé Cette thèse est consacrée à un nouveau modèle d'apparence pour la
segmentation d'images basée modèle. Ce modèle, dénommé Multimodal Prior Appearance …