基于MR的左心房纤维化区域分割与重建
Segmentation and Reconstruction of Left Atrial Fibrosis Based on MR
贾子煜 1黄欢 1胡春艾 2窦丽娜2
作者信息
- 1. 江苏师范大学电气工程及自动化学院,江苏 徐州 221000
- 2. 徐州市中心医院影像科,江苏 徐州 221000
- 折叠
摘要
目前主流的左心房纤维化区域分割方法是先手动划分心房壁区域,再在心房壁区域内使用阈值法提取纤维化部分.这不仅需要操作者具有专业的背景知识,同时工作量也较大,而且阈值法也难以同时对轻重程度不同的纤维化区域进行精确分割.为了解决上述问题,本文提出一种新的基于MR图像纤维化区域分割方法.首先使用拉普拉斯锐化算法,提高纤维化区域的对比度,同时采用核相关滤波算法对目标区域进行跟踪,从而去除心房外的组织;其次比较区域增长法、活动轮廓法以及基于Hessian矩阵的分割算法对纤维化区域的分割效果,选出效果最优的分割方法;最后对纤维区域的三维点云数据进行重建与渲染.实验结果表明,该方法无需逐图手动划分心房壁区域,且分割结果具有较高的准确度,可以更好地帮助医生对相关疾病进行诊断.
Abstract
The current mainstream segmentation method for left atrial fibrosis is to manually divide the atrial wall area first,and then use threshold method to extract the fibrosis part within the atrial wall area.This not only requires the operator to have profes-sional background knowledge,but also requires a large workload,and the threshold method is also difficult to accurately seg-ment fibrosis areas with different degrees of severity at the same time.To address the above issues,this paper proposes a new method for segmenting fibrotic regions in MR images.Firstly,the Laplace sharpening algorithm is used to improve the contrast of the fibrotic area,while the kernel correlation filtering algorithm is used to track the target area to remove tissue outside the atrium;Secondly,the segmentation effects of region growth method,active contour method,and Hessian matrix based segmenta-tion algorithm on fibrotic regions were compared,and the most effective segmentation method was selected;Finally,we recon-struct and render the 3D point cloud data of the fiber region.The experimental results show that this method does not require manual segmentation of the cardiac atrial wall region by image,and the segmentation results have high accuracy,which can bet-ter assist doctors in diagnosing related diseases.
关键词
MR图像/心房纤维化/图像增强/目标跟踪/分割算法Key words
magnetic resonance imaging/atrial fibrosis/image enhancement/target tracking/segmentation algorithm引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据