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
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;
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
DOI :
10.1109/ICBBE.2009.5162435