The automatic segmentation of the prostate and rectum from 3-D computed tomography (CT) images is still a challenging problem, and is critical for image-guided therapy application...
We propose a new supervised texture segmentation and classification technique based on combining features extracted from the discrete wavelet frames of an image (specifically, the...
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...
Traditional photometric stereo algorithms employ a Lambertian reflectance model with a varying albedo field and involve the appearance of only one object. In this paper, we gene...
Shaohua Kevin Zhou, Gaurav Aggarwal, Rama Chellapp...
A general framework for performing robust, unsupervised tissue classification in magnetic resonance images is presented. Tissue classification is formulated as an estimation probl...