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基于模型的MRI扫描图像上前连合和后连合的自动检测

Model-based automatic detection of the anterior and posterior commissures on MRI scans.

作者信息

Ardekani Babak A, Bachman Alvin H

机构信息

Center for Advanced Brain Imaging, The Nathan S. Kline Institute for Psychiatric Research, 140 Old Orangeburg Road, Orangeburg, NY 10962, USA.

出版信息

Neuroimage. 2009 Jul 1;46(3):677-82. doi: 10.1016/j.neuroimage.2009.02.030. Epub 2009 Mar 3.

DOI:10.1016/j.neuroimage.2009.02.030
PMID:19264138
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2674131/
Abstract

The projections of the anterior and posterior commissures (AC/PC) on the mid-sagittal plane of the human brain are important landmarks in neuroimaging. They can be used, for example, during MRI scanning for acquiring the imaging sections in a standard orientation. In post-acquisition image processing, these landmarks serve to establish an anatomically-based frame of reference within the brain that can be extremely useful in designing automated image analysis algorithms such as image segmentation and registration methods. This paper presents a fully automatic model-based algorithm for AC/PC detection on MRI scans. The algorithm utilizes information from a number of model images on which the locations of the AC/PC and a reference point (the vertex of the superior pontine sulcus) are known. This information is then used to locate the landmarks on test scans by template matching. The algorithm is designed to be fast, robust, and accurate. The method is flexible in that it can be trained to work on different image contrasts, optimized for different populations, or scanning modes. To assess the effectiveness of this technique, we compared automatically and manually detected landmark locations on 84 T(1)-weighted and 42 T(2)-weighted test scans. Overall, the average Euclidean distance between automatically and manually detected landmarks was 1.1 mm. A software implementation of the algorithm is freely available online at www.nitrc.org/projects/art.

摘要

前连合和后连合(AC/PC)在人脑正中矢状面上的投影是神经影像学中的重要标志。例如,在MRI扫描期间,它们可用于获取标准方向的成像切片。在采集后的图像处理中,这些标志有助于在脑内建立基于解剖结构的参考框架,这在设计诸如图像分割和配准方法等自动图像分析算法时非常有用。本文提出了一种基于模型的全自动算法,用于在MRI扫描上检测AC/PC。该算法利用了一些模型图像的信息,这些模型图像上AC/PC和一个参考点(脑桥背侧沟顶点)的位置是已知的。然后,通过模板匹配利用这些信息在测试扫描上定位这些标志。该算法设计得快速、稳健且准确。该方法具有灵活性,因为它可以经过训练以处理不同的图像对比度,针对不同人群或扫描模式进行优化。为了评估该技术的有效性,我们在84张T(1)加权和42张T(2)加权测试扫描上比较了自动检测和手动检测的标志位置。总体而言,自动检测和手动检测的标志之间的平均欧几里得距离为1.1毫米。该算法的软件实现可在www.nitrc.org/projects/art上免费在线获取。

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