重庆邮电大学学报（自然科学版）2024，Vol.36Issue(4)：687-696,10.DOI:10.3979/j.issn.1673-825X.202310290348
基于改进非洲秃鹫优化算法的脑MRI图像分割
Brain MRI image segmentation based on improved African vulture optimization algorithm
摘要
Abstract
Addressing the imbalance between exploitation and exploration capabilities in the African vulture optimization al-gorithm(AVOA),we propose an improved African vulture optimization algorithm(IAVOA)incorporating multiple strate-gies.This algorithm employs the good point set method to initialize the population for enhanced diversity,introduces mixed opposition-based learning to strengthen exploitation and exploration,implements an adaptive trustworthiness strategy for dy-namically adjusting the search process,and applies Gaussian mutation to further balance the exploitation and exploration ca-pabilities of the algorithm.Simulation results demonstrate that,compared to competing algorithms,IAVOA significantly im-proves convergence speed,solution accuracy,and stability on 12 typical test functions.Furthermore,this paper proposes the IAVOA-FCM algorithm for brain MRI image segmentation in small sample datasets,optimizing the FCM algorithm through the powerful global optimization capability of the IAVOA.In the experiments for brain magnetic resonance imaging(MRI)image segmentation,compared to five other advanced hybrid algorithms,IAVOA-FCM exhibits significant advanta-ges in segmentation accuracy,stability,and other aspects.关键词
非洲秃鹫优化算法/模糊C均值/群智能优化算法/信任度策略/脑磁共振成像(MRI)图像分割Key words
African vulture optimization algorithm/fuzzy c-means/swarm intelligence optimization algorithm/trust degree strategy/brain magnetic resonance imaging image(MRI)segmentation分类
信息技术与安全科学引用本文复制引用
王豪,凌基伟,陈昊,黄志勇,王岫鑫..基于改进非洲秃鹫优化算法的脑MRI图像分割[J].重庆邮电大学学报（自然科学版）,2024,36(4):687-696,10.基金项目
国家自然科学基金项目(61605021) （61605021）
重庆市教委科学技术研究项目(KJZD-K202300614) （KJZD-K202300614）
中国博士后科学基金第74 批面上资助项目(2023MD744138) （2023MD744138）
重庆市自然科学基金面上项目(CSTB2023NSCQ-MSX0839)The National Natural Science Foundation of China(61605021) （CSTB2023NSCQ-MSX0839）
The Science and Technology Research Program Project of Chongqing Municipal Education Commission(KJZD-K202300614)) （KJZD-K202300614）
The 74th Grant from China Postdoctoral Science Foun-dation Project(2023MD744138) （2023MD744138）
The Chongqing Natural Science Foundation Project(CSTB2023NSCQ-MSX0839) （CSTB2023NSCQ-MSX0839）
