CAJ | 학술논문

为解决心脏CT图像序列传统分割方法人工交互复杂、效率低的问题，提出一种模糊水平集分割方法。只需选定单张心脏CT图像，利用改进后的模糊聚类算法获取感兴趣区域初始轮廓，将其结果用于引导C‐V模型水平集进行心脏组织精准分割。为有效减少图像序列分割时间及人工交互，由单张图像分割结果作为其空间相邻图像水平集的初始轮廓，避免重复性聚类过程，循环迭代得到每张图像最终轮廓位置。实验结果表明，该算法能准确分割出心脏各组织边缘，时间代价小、人工交互简单，分割结果能为心脏三维重建提供准确的数据集。
위해결심장CT도상서열전통분할방법인공교호복잡、효솔저적문제，제출일충모호수평집분할방법。지수선정단장심장CT도상，이용개진후적모호취류산법획취감흥취구역초시륜곽，장기결과용우인도C‐V모형수평집진행심장조직정준분할。위유효감소도상서렬분할시간급인공교호，유단장도상분할결과작위기공간상린도상수평집적초시륜곽，피면중복성취류과정，순배질대득도매장도상최종륜곽위치。실험결과표명，해산법능준학분할출심장각조직변연，시간대개소、인공교호간단，분할결과능위심장삼유중건제공준학적수거집。
A fuzzy level set segmentation method was proposed to solve the complexity and low efficiency problems of the conven‐tional cardiac CT image sequence segmentation method .This method could be realized only by selecting a single cardiac CT ima‐ges ,and using the improved fuzzy clustering algorithm to extract the initial outline of the region of interest (ROI) .Its results were used to guide the C‐V model level set for cardiac tissues precise segmentation .To effectively reduce the time cost for image sequence segmentation and human interaction ,each segmentation result was used as the initial contour of its adjacent images . This access avoided the repetitive clustering process ,and the final outline of the image was obtained .Experimental results demonstrate that the algorithm can accurately segment the edge of the heart organization with less time and simple human interaction .Besides ,the segmentation results can provide accurate data set for the three‐dimensional heart reconstruction .