Title :
Glomerulus extraction by using genetic algorithm for edge patching
Author :
Ma, Jiaxin ; Zhang, Jun ; Hu, Jinglu
Author_Institution :
Grad. Sch. of Inf., WASEDA Univ., Kitakyushu
Abstract :
Glomerulus is the filtering unit of the kidney. In the computer aided diagnosis system designed for kidney disease, glomerulus extraction is an important step for analyzing kidney-tissue image. Against the disadvantages of traditional methods, this paper proposes a glomerulus extraction method using genetic algorithm for edge patching. Firstly, Canny edge detector is applied to get discontinuous edges of glomerulus. After labeling to remove the noises, genetic algorithm is used to search for optimal patching segments to join those edges together. Lastly, the edges and the patching segments with high fitness would be able to form the whole edge of the glomerulus. Experiments and comparisons indicate the proposed method can extract the glomerulus from kidney-tissue image both fast and accurately.
Keywords :
edge detection; feature extraction; filtering theory; genetic algorithms; image segmentation; kidney; medical image processing; patient diagnosis; Canny edge detection; computer aided diagnosis system; glomerulus extraction; kidney-tissue image; optimal patching segment; Data mining; Detectors; Diseases; Genetic algorithms; Image analysis; Image edge detection; Labeling; Noise shaping; Production systems; Shape;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983251