DocumentCode
3220597
Title
Analysis of brain scan images using genetic algorithms
Author
Hogans, John Ed, IV ; Homaifar, Abdollah
Author_Institution
North Carolina A&T State Univ., Greensboro, NC, USA
fYear
1993
fDate
7-9 Mar 1993
Firstpage
218
Lastpage
222
Abstract
Genetic algorithms are used to automatically quantify the three types of brain tissue: cerebrospinal fluid (CSF), white matter, and gray matter. The quantification technique utilizes a statistical model of the noise and partial volume effect, and fits a derived probability density function to that of the data. The results are compared with those obtained by a tree annealing algorithm
Keywords
biomedical NMR; brain models; genetic algorithms; medical image processing; CSF; brain scan images; cerebrospinal fluid; genetic algorithms; gray matter; noise; partial volume effect; probability density function; quantification; statistical model; tree annealing algorithm; white matter; Algorithm design and analysis; Biological cells; Brain; Genetic algorithms; Image analysis; Magnetic analysis; Magnetic resonance imaging; Optimization methods; Pixel; Probability density function;
fLanguage
English
Publisher
ieee
Conference_Titel
System Theory, 1993. Proceedings SSST '93., Twenty-Fifth Southeastern Symposium on
Conference_Location
Tuscaloosa, AL
ISSN
0094-2898
Print_ISBN
0-8186-3560-6
Type
conf
DOI
10.1109/SSST.1993.522774
Filename
522774
Link To Document