In this paper, we propose a Bayesian approach to video object segmentation. Our method consists of two stages. In the first stage, we partition the video data into a set of 3D wate...
We present a novel approach to the segmentation and analysis of vasculature from volumetric medical image data. Our method is an adoption and significant extension of deformable o...
Probabilistic models are extensively used in medical image segmentation. Most of them employ parametric representations of densities and make idealizing assumptions, e.g. normal di...
Generating realistic geometric models from 3D segmented images is an important task in many biomedical applications. Segmented 3D images impose particular challenges for meshing a...
Extracting 3D structures from volumetric images like MRI or CT is becoming a routine process for diagnosis based on quantitation, for radiotherapy planning, for surgical planning a...