DocumentCode
2500233
Title
Band Selection for Biomedical Hyperspectral Data Studies Using Genetic Algorithms
Author
Chunni Dai ; Qingli Li ; Jingao Liu
Author_Institution
Key Lab. ofPolor Mater. & Devices, East China Normal Univ., Shanghai, China
fYear
2009
fDate
11-13 June 2009
Firstpage
1
Lastpage
4
Abstract
Hyperspectral imaging coupled with microscopy has been introduced for biomedicine science recently. As hyperspectral data cube include a great deal of single-band images, an adaptive genetic algorithm is presented to solve the best band combination problem for hyperspectral biomedical image studies in this paper. Simulation result demonstrates the effect of this algorithm to the hyperspectral image of leukemia blood cell.
Keywords
biomedical optical imaging; cancer; cellular biophysics; genetics; optical microscopy; tumours; band combination problem; biomedical hyperspectral imaging; genetic algorithm; leukemia blood cell image; optical microscopy; single-band image; Biomedical imaging; Biomedical optical imaging; Blood; Cells (biology); Encoding; Genetic algorithms; Hyperspectral imaging; Hyperspectral sensors; Optical microscopy; Principal component analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-2901-1
Electronic_ISBN
978-1-4244-2902-8
Type
conf
DOI
10.1109/ICBBE.2009.5162435
Filename
5162435
Link To Document