This work presents an efficient and automated method to extract the human cerebral ventricular system from MRI driven by anatomic knowledge. The ventricular system is divided into ...
Yan Xia, Qingmao Hu, Aamer Aziz, Wieslaw Lucjan No...
A general framework for performing robust, unsupervised tissue classification in magnetic resonance images is presented. Tissue classification is formulated as an estimation probl...
— A robust fully automatic method for segmenting the brain from head magnetic resonance (MR) images has been developed, which works even in the presence of radio frequency (RF) i...
Intensity inhomogeneities often occur in real-world images and may cause considerable difficulties in image segmentation. In order to overcome the difficulties caused by intensity ...
Chunming Li, Chiu-Yen Kao, John C. Gore, Zhaohua D...
Abstract. We propose a deep study on tissue modelization and classification Techniques on T1-weighted MR images. Three approaches have been taken into account to perform this valid...