CAJ | 학술논문

人脑 MR 图像中的海马结构存在低对比度、边界模糊等缺点，给海马的轮廓分割带来较大干扰。为解决水平集分割海马时边界容易停留在非目标区域梯度极值处的问题，提出一种改进的水平集方法。从图像全局出发考虑方差信息，在水平集函数的外部能量泛函中增加波动能量项，驱动零水平集曲线向灰度波动较小的区域运动。实验结果表明，该方法可提取出 MR 图像中的海马轮廓，分割效果较好，演化速度有所提高。
인뇌 MR 도상중적해마결구존재저대비도、변계모호등결점，급해마적륜곽분할대래교대간우。위해결수평집분할해마시변계용역정류재비목표구역제도겁치처적문제，제출일충개진적수평집방법。종도상전국출발고필방차신식，재수평집함수적외부능량범함중증가파동능량항，구동령수평집곡선향회도파동교소적구역운동。실험결과표명，해방법가제취출 MR 도상중적해마륜곽，분할효과교호，연화속도유소제고。
The contour extraction of hippocampus in human brain MR images has a lot of interference which is caused by its low contrast, fuzzy boundaries, and so on. To solve this problem that the boundary stays at gradient extremal in non-target area when level set segmentation method is applied, in this paper, a method based on improved level set is proposed. It considers the variance information through the whole image, adds wave energy items in the external energy functional of the level set function, and drives the zero level set curve to where gray-scale fluctuation is smaller relative to the hippocampus. Experimental results show that this method can ideally extract the contour of the hippocampus from the MR images with excellent segmentation results and greatly improves the evolution speed.