Liwei Chen
ABSTRACT
Pigeons have strong disease resistance and short reproductive cycle. It is an ideal sample for bird research. It has been widely used in scientific research and related experiments in the fields of biology, neurology, and medicine. Generally, after obtaining pigeon brain slices or images, a segmentation algorithm is used to extract brain tissue for further research. The segmentation accuracy of the algorithm has always been the focus and difficulty in the research. This paper used Otsu algorithm, fuzzy threshold segmentation algorithm, K-means algorithm and improved particle swarm algorithm to segment pigeon brain tissue. We calibrated the area of pigeon brain tissue by comparing the segmented image with the labeled pigeon brain tissue. According to certain evaluation criteria, the accuracy of brain tissue segmentation in different MRI images was calculated. By comparing the accuracy of each tissue segmentation, we can quantitatively judge the segmentation effect of the algorithm. Comprehensive analysis showed that the improved particle swarm optimization algorithm had a better segmentation effect.
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Index Terms
- An Improved Particle Swarm Optimization Algorithm for Pigeon Brain Tissue MRI Image Segmentation
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