Remote brain image segmentation

Author

Kelle, Olavi

fYear

1999

fDate

1999

Firstpage

22

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ITAB.1999.842313

Filename

842313