Segmentation of medical images is commonly formulated as a supervised learning problem, where manually labeled training data are summarized using a parametric atlas. Summarizing th...
Mert R. Sabuncu, B. T. Thomas Yeo, Koen Van Leem...
This paper presents e cient and portable implementations of a useful image enhancement process, the Symmetric Neighborhood Filter SNF, and an image segmentation technique which ma...
We introduce a novel approach for magnetic resonance image (MRI) brain tissue classification by learning image neighborhood statistics from noisy input data using nonparametric den...
Tolga Tasdizen, Suyash P. Awate, Ross T. Whitaker,...
: Planar patch detection aims at simplifying data from 3-D imaging sensors to a more compact scene description. We propose a fusion of intensity and depth information using Graph-C...
The Hierarchical Conditional Random Field (HCRF) model have been successfully applied to a number of image labeling problems, including image segmentation. However, existing HCRF m...
Xavier Boix, Josep M. Gonfaus, Joost van de Weijer...