Medical Image Segmentation Based on Wavelet Transformation and Watershed Algorithm
The automation edge extraction of glomerulus is an important step for analyzing kidney-tissue image in the computer aided diagnosis system of kidney disease. According to the characteristic of these medical images, this paper proposes a glomerulus extraction method based on wavelet transformation and watershed algorithm. First, a LOG filter is applied to the low-resolution image, which corresponds to low frequency sub band after wavelet transformation, so that rough edge information can be obtained. After labeling to remove the noises and thinning, a genetic algorithm is applied to search the best fitting curve, which determines the barycenter position of glomerulus and sets this barycenter as seed. Secondly, the image which contains complete object boundary can be obtained through watershed transform, after region growing operation, glomerulus region can be extracted. With abundant samples, experimental result indicates our method can extract the glomerulus from kidney-tissue image both accurately and availably.
Glomerulus wavelet transformation genetic algorithm watershed algorithm
Jun Zhang Jiulun Fan
Department of Information and Control Xian Institute of Post and Telecommunications Xian, Shannxi Province, China
国际会议
2006 IEEE International Conference on Information Acquisition
山东威海
英文
484-488
2006-08-20（万方平台首次上网日期，不代表论文的发表时间）