Reconstruction of Partial Liver Shapes Based on a Statistical 3D Shape Model
Abstract
Statistical shape models (SSM) describe complex shape variations derived from a training population in a compact way. Thus, they are well suited for robust reconstruction of unknown shapes, especially insituations where data is affected by noise, artefacts, or only partially contains the unknown shape. Important applications are, e.g., image segmentation as well as reconstructive surgery. The aim of this work is to provide an automatic method to reconstruct and complete partial liver surfaces.
Type
Publication
Proc. Symposium on Statistical Shape Models & Applications (SHAPE), 2015
This work won the Shape Challenge Best Prize, sponsored by sponsored by Siemens.
Hans Lamecker
Managing Director
Advancing 3D analysis, planning, design and manufacturing using innovative computational methods and tools