| ORIGINAL ARTICLE |
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| Year : 2019 | Volume
: 3
| Issue : 1 | Page : 5-8 |
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Medical image segmentation method based on the improved artificial bee colony algorithm
LF Li1, MR Qi2
1 Department of Medicine, School of Computer Science, Shaanxi Normal University, Xi'an, China
2 Department of Medicine, Xi'an University of Science and Technology, College of Humanities and Foreign Languages, Xi'an, China
Correspondence Address:
Dr. L F Li
School of Computer Science, Shaanxi Normal University, Xi'an 710119
China
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/MTSP.MTSP_2_19
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Objectives: The aim is to study the application of artificial bee colony (ABC) algorithm in medical image threshold segmentation. Methods: A new image segmentation method based on the improved ABC and thresholding medical image threshold segmentation method is proposed, which is variable coefficient ABC (VCABC) optimization algorithm, which is used to determine n-1 optimal n level threshold on a given image. The proposed method is compared with the Particle Swarm Optimization fractional image threshold segmentation method and the ABC fractional medical image threshold segmentation method. Results: When considering a variety of conditions, the performance of this method is better than that of other methods. Conclusions: The improved method of combining ABC and fractional medical image threshold segmentation method is effective.
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