Glomerulus Extraction Based on Genetic Algorithm and Watershed Transform

Glomerulus extraction is an important step for analyzing kidney-tissue image in the computer aided diagnosis system of kidney disease. According to the characteristic of these images, this paper proposes a glomerulus extraction method based on genetic algorithm and watershed transform. Firstly, a LOG filter is applied to get binary images that contain less noise by adjusting the parameters of Gaussian function. After labeling to remove the noises and thinning, a genetic algorithm is applied to these preprocessing images to search the best fitting curve, which determines the barycenter position of glomerulus and set 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

Authors

• Jun Zhang
• Jiulun Fan 0001

Keywords

• Genetic algorithms
• Data mining
• Filters
• Shape
• Biological cells
• Image analysis
• Diseases
• Humans
• Biopsy
• Spline
• Watershed Segmentation
• NSFC Grant
• Best Fit
• Binary Image
• Barycenter
• Computer-aided Diagnosis System
• Contrast Agent
• Local Solution
• Part Of The Image
• Interior Point
• Lines Of Point
• Filter Parameters
• Distance Map
• Digital Image Processing
• Degree Of Approximation
• Image Gradient
• Genetic Operators
• Influence Of Different Factors
• Closed Curve
• Glomerulus
• LOG filter
• genetic algorithm
• watershed transform
• image segmentation