Title :
Remote brain image segmentation
Abstract :
Quantitative analysis of brain magnetic resonance (MR) images requires methods of tissue classification. New Web and Internet technologies allow remote MR image classification and visualization through browser functionality. Our application uses a method of segmentation based on the Markov random field (MRF) modeling of maximum a-posteriori (MAP) probability. The result of the segmentation can also be visualised as a VRML (Virtual Reality Modeling Language) world
Keywords :
Internet; Markov processes; biomedical MRI; brain; data visualisation; image classification; image segmentation; information resources; maximum likelihood estimation; medical image processing; probability; telemedicine; virtual reality; Internet; Markov random field; VRML; Virtual Reality Modeling Language; Webbrowser functionality; World Wide Web; brain MRI; data visualization; maximum a-posteriori probability; quantitative analysis; remote brain image segmentation; tissue classification; virtual world; Brain; Image analysis; Image classification; Image segmentation; Internet; Magnetic analysis; Magnetic resonance; Markov random fields; Maximum a posteriori estimation; Visualization;
Conference_Titel :
Information Technology Applications in Biomedicine, 1999. ITIS-ITAB '99. 1999 IEEE EMBS International Conference on
Conference_Location :
Amsterdam
Print_ISBN :
0-7803-5647-0
DOI :
10.1109/ITAB.1999.842313
