JOURNAL ARTICLE

Medical Image Segmentation Based on Genetic Algorithm

Abstract

As one of the difficulties and hot of computer vision and image processing. Image segmentation is highly valued by the research workers. In this paper, Genetic Algorithm (GA) has proposed to segment the image. With global searching capacity and the largest variance between clusters as the fitness function, this method can search the optimal threshold of edge detection automatically, and extract the edge of image by combining morphologic processing to realize the segmentation. Experiment shows that the method can not only simplify the segmentation, but also achieve a good segmentation effect and can improve the efficiency and quality of the picture to some extent. The results show that GA algorithm is very stable, and the fusion result is more satisfactory. Thus, GA can be applied in image segmentation and it has a good foreground in application in image processing.

Keywords:
Image segmentation Scale-space segmentation Segmentation-based object categorization Fitness function Artificial intelligence Computer science Genetic algorithm Segmentation Minimum spanning tree-based segmentation Computer vision Image texture Region growing Image processing Image (mathematics) Range segmentation Pattern recognition (psychology) Enhanced Data Rates for GSM Evolution Machine learning

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Topics

Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Industrial Vision Systems and Defect Detection
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering
Image and Object Detection Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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