基于磁共振成像的无分割皮质厚度测量
SEGMENTATION-FREE MEASURING OF CORTICAL THICKNESS FROM MRI.
作者信息
Aganj Iman, Sapiro Guillermo, Parikshak Neelroop, Madsen Sarah K, Thompson Paul M
机构信息
Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, USA.
Laboratory of Neuro Imaging, University of California-Los Angeles, School of Medicine, Los Angeles, CA 90095, USA.
出版信息
Proc IEEE Int Symp Biomed Imaging. 2008 May;2008:1625-1628. doi: 10.1109/ISBI.2008.4541324.
Estimating the thickness of cerebral cortex is one of the most essential measurements performed in MR brain imaging. In this work we present a new approach to measure the cortical thickness which is based on minimizing line integrals over the probability map of the gray matter in the MRI volume. Previous methods often perform a pre-segmentation of the gray matter before measuring the thickness. Considering the noise and the partial volume effects, there are underlying class probabilities allocated to each voxel that this hard classification ignores, a result of which is a loss of important available information. Following the introduction of the proposed framework, the performance of our method is demonstrated on both artificial volumes and real MRI data for normal and Alzheimer affected subjects.
估计大脑皮层厚度是磁共振脑成像中最基本的测量之一。在这项工作中，我们提出了一种测量皮层厚度的新方法，该方法基于在MRI体积中灰质概率图上最小化线积分。以前的方法在测量厚度之前通常会对灰质进行预分割。考虑到噪声和部分容积效应，每个体素都有潜在的类别概率，而这种硬分类忽略了这些概率，其结果是丢失了重要的可用信息。在介绍了所提出的框架之后，我们在正常和阿尔茨海默病患者的人工体积和真实MRI数据上展示了我们方法的性能。
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