DocumentCode :
671778
Title :
Multi-circle detection for bladder cancer diagnosis based on artificial immune systems
Author :
Dingran Lu ; Xiao-Hua Yu
Author_Institution :
Dept. of Electr. Eng., California Polytech. State Univ., San Luis Obispo, CA, USA
fYear :
2013
fDate :
4-9 Aug. 2013
Firstpage :
1
Lastpage :
7
Abstract :
Bladder cancer is the fourth most common type of cancer in men and the ninth in women in United States. A recent approach for early bladder cancer detection is to mix human urine samples with some very small beads that are coated with special biochemical materials which can bind to tumor cells, but not to normal cells. By examining and analyzing bead images of urine samples under a microscope, patients with potential cancer risk can be identified. Multi-circle detection is a challenging problem for processing bead images in an automatic bladder cancer diagnosis system, due to the large number and non-ideal shapes of objects (e.g., beads with cancer cells) in microscope images. In this study, a new approach based on real valued artificial immune system is developed and tested. Computer simulation results show that this algorithm outperforms traditional methods such as circular Hough Transform and geometric characteristic based methods in terms of both precision and robustness.
Keywords :
artificial immune systems; cancer; medical image processing; microscopes; object detection; automatic bladder cancer diagnosis system; bead image processing; microscope images; multicircle detection; real valued artificial immune system; Bladder; Cancer; Image edge detection; Immune system; Sensitivity; Shape; Transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2013 International Joint Conference on
Conference_Location :
Dallas, TX
ISSN :
2161-4393
Print_ISBN :
978-1-4673-6128-6
Type :
conf
DOI :
10.1109/IJCNN.2013.6707120
Filename :
6707120
Link To Document :
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