中圖分類號(hào)： TN92,；TP391 文獻(xiàn)標(biāo)識(shí)碼： A DOI：10.16157/j.issn.0258-7998.191116 中文引用格式： 徐浩,，王霜. 云螢火蟲(chóng)算法改進(jìn)二維Tsallis熵的醫(yī)學(xué)圖像分割[J].電子技術(shù)應(yīng)用，2020,，46(6)：73-76,，81. 英文引用格式： Xu Hao，Wang Shuang. Medical image segmentation using two-dimensional Tsallis entropy improved by cloud model firefly algorithm[J]. Application of Electronic Technique,，2020,，46(6)：73-76，81.
Medical image segmentation using two-dimensional Tsallis entropy improved by cloud model firefly algorithm
Xu Hao1,，Wang Shuang2
1.Department of Optometry,，Wenzhou Medical University,Wenzhou 325000，China,； 2.Xi′an University of Science and Technology,，Xi′an 710054，China
Abstract： In order to improve the effect of medical image segmentation, for the effect of two-dimensional Tsallis entropy threshold method,，two-dimensional Tsallis Entropy improved by cloudmodel firefly algorithm is applied to medical image segmentation algorithm. Firstly, in order to improve the convergence speed and optimization ability,，the cloud model is introduced into the Firefly algorithm. Secondly, the homogeneity measure was chosen as the evaluation index of medical image segmentation, and the parameter q of the two-dimensional Tsallis entropy threshold method was optimized by CMFA algorithm. The results show that CMFA-Tsallis has the highest homogeneity measure compared with FA-Tsallis and Tsallis, and the result boundary is clear, thus proving the effectiveness of this algorithm.
Key words : medical image；image segmentation,；Tsallis entropy,；firefly algorithm；cloud model
