CAJ | 학술논문

针对CT医学图像灰度不均匀的特点，研究了基于改进的模糊聚类和Chan-Vese模型的图像分割。该分割模型综合利用基于空间信息的FCM算法、图像局部区域信息以及Chan-Vese模型，通过最小化能量函数的方式来进行曲线演化。基于空间信息的FCM算法对曲线的演化起到了一定的收敛作用，并且局部区域信息提高了分割质量。分割模型还考虑了分割效果和计算效率，降低了算法的时间复杂度，提高了算法的执行效率，从而提高了灰度不均匀图像分割的精度。
침대CT의학도상회도불균균적특점，연구료기우개진적모호취류화Chan-Vese모형적도상분할。해분할모형종합이용기우공간신식적FCM산법、도상국부구역신식이급Chan-Vese모형，통과최소화능량함수적방식래진행곡선연화。기우공간신식적FCM산법대곡선적연화기도료일정적수렴작용，병차국부구역신식제고료분할질량。분할모형환고필료분할효과화계산효솔，강저료산법적시간복잡도，제고료산법적집행효솔，종이제고료회도불균균도상분할적정도。
Due to the inhomogeneous density of CT medical image, the segmentation model based on the local fuzzy clustering method and Chan-Vese model is investigated. This segmen-tation model makes full use of the spatial fuzzy c-means ( SFCM) algorithm,the local region in-formation,and local Chan-Vese model. The curve evolution is realized by minimizing the energy function. SFCM algorithm is convenient for controlling level set evolution and calculation con-vergence,and the local image information can improve the quality of segmentation. Moreover, the segmentation model considers the effectiveness of segmentation and high efficiency to re-duce the time complexity of the algorithm. Thus,the segmentation model gets more precise re-sult of image segmentation for the inhomogeneous density of CT medical image.