首页> 外文会议>Image Processing pt.2; Progress in Biomedical Optics and Imaging; vol.6 no.24 >Localization of Perfusion Abnormalities in Brain SPECT Imaging
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Localization of Perfusion Abnormalities in Brain SPECT Imaging

机译:脑SPECT成像中灌注异常的定位

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SPECT (Single Photon Emission Computed Tomography) imagery has become widely available and is particularly useful for regional cerebral blood flow (rCBF) studies. Distribution of rCBF is still essentially studied by visual observation, searching for abnormalities, and comparing with other studies. In order to facilitate the localization of these abnormalities, we propose a simple, automatic and direct method to register a SPECT rCBF study with a commonly used atlas in the neurological community, the Talairach Atlas. The Talairach atlas still gives today the most extensive information of regions of interests, coupled with a coordinate system. The proposed method will therefore allow a physician to precisely navigate in a SPECT image by interpreting the abnormalities coordinates. The registration of these two volumes is carried out in two steps, a rough alignment followed by an elastic registration. The rough alignment step consists in computing the mass centroid of each volume and in scaling the volumes accordingly if necessary. A simple threshold method (30% of the maximum intensity of the SPECT image) is used to determine the volume of the brain being studied. In order to facilitate the fine registration, the Talairach atlas was previously segmented in three classes: cerebrospinal fluid (CSF), white and gray matters. Then, an automatic intensity transformation as well as a low-pass filtering is performed to closely resemble the spatial resolution and intensities of the SPECT volume. This intensity transformation is a simple method which combines the use of a joint 2D histogram of the segmented atlas and the individual volume as well as a clustering algorithm. The fine registration is then computed with an optical flow methodology. The effectiveness of this scheme was tested on a database of virtual patients, simulated from a database of 45 healthy and diseased brains. The rate of pixels misclassification in each class within a one pixel neighborhood (CSF 0.5%; white matter 1.37%, gray matter 2.80%) indicates that this proposed method will be useful for the nuclear physician in helping localize abnormalities.
机译:SPECT(单光子发射计算机断层扫描)图像已得到广泛使用,对于区域脑血流(rCBF)研究特别有用。仍通过肉眼观察,寻找异常并与其他研究进行比较来研究rCBF的分布。为了促进这些异常的定位,我们提出了一种简单,自动和直接的方法来将SPECT rCBF研究注册到神经病学界常用的地图集Talairach Atlas中。 Talairach地图集今天仍然提供感兴趣区域的最广泛信息,以及一个坐标系统。因此,所提出的方法将允许医生通过解释异常坐标来在SPECT图像中精确导航。这两个体积的配准分两个步骤进行,先进行粗调,然后进行弹性配准。粗对准步骤包括计算每个体积的质心,并在必要时相应地缩放体积。一种简单的阈值方法(SPECT图像最大强度的30%)用于确定正在研究的大脑的体积。为了便于精细定位,以前将Talairach地图集分为三类:脑脊液(CSF),白色和灰色物质。然后,执行自动强度转换以及低通滤波,以非常类似于SPECT体积的空间分辨率和强度。这种强度变换是一种简单的方法,将分割后的地图集和单个体积的联合2D直方图的使用与聚类算法结合在一起。然后使用光流方法计算精细配准。该方案的有效性在虚拟患者数据库中进行了测试,该数据库由45个健康和患病大脑的数据库模拟而成。在一个像素邻域内(CSF为0.5%;白质为1.37%,灰质为2.80%),每个类别中像素的错误分类率表明,该建议的方法将有助于核医师帮助定位异常。

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