Title :
Genetic algorithm for edge extraction of glomerulus area
Author :
Zhang, Jun ; Zhu, Hong ; Qian, Xueming ; Huang, Tao
Author_Institution :
Inst. of Inf. & Autom. Eng., Xi´´an Univ. of Technol., China
Abstract :
The automatic analysis of kidney-tissue image is an important subsystem in the computer aided diagnosis system of kidney disease. In this subsystem, the correct extraction of glomerulus is an important premise to the exact analysis of kidney-tissue image. A glomerulus edge extraction method based on genetic algorithm (GA) is proposed by considering complex characteristics of the image. Firstly, different scale binary images are obtained by adjusting the parameters of LOG filter. Secondly, the crude spline curve fitting for the glomerulus area boundary is got by genetic algorithm based on the small-scale binary image. Thirdly, elaborate adjustment of spline fitting curve is performed according to more boundary information of large-scale binary image to get the optimal spline curve. Finally, the glomerulus area can be extracted correctly according to the fitting curve. Experimental result indicates high precision of glomerulus edge extraction from the kidney-tissue image.
Keywords :
curve fitting; diseases; edge detection; feature extraction; filtering theory; genetic algorithms; image segmentation; kidney; medical image processing; search problems; splines (mathematics); LOG filter parameters; automatic kidney-tissue image analysis; computer aided diagnosis system; genetic algorithm; glomerulus area edge extraction; image segmentation; kidney disease; large-scale binary image; optimal spline curve fitting; region extraction; small-scale binary image; Automation; Biopsy; Curve fitting; Data mining; Diseases; Filters; Genetic algorithms; Image analysis; Pathology; Spline;
Conference_Titel :
Information Acquisition, 2004. Proceedings. International Conference on
Print_ISBN :
0-7803-8629-9
DOI :
10.1109/ICIA.2004.1373383
