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EM algorithm based intervertebral disc segmentation on MR images

机译:基于EM算法在MR图像上的椎间盘分割

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Image segmentation is well known in partitioning a digital image into several segments. Recent days lower back pain in human being increases and so the lumber spine pathology detection becomes a predominant research area in Computer Aided Diagnosis (CAD) system. In the process of lumbar spine pathology detection, the segmentation of the Intervertebral Disc (IVD) is the major step as it identifies the IVDs or the boundaries of the IVDs either normal or abnormal in images. When the axial or the sagittal View of lumbar spine MR image is given as input, this proposed work segments the IVD in both the axial and sagittal views. The segmentation of IVD is a four stage process. First, Expectation-Maximization (EM) segmentation is performed on the MR Image. EM segmentation yields an advantage over K-means with the case of the size of clustering. The second stage is to carry out the morphological operators and third, apply edge detection method and obtain the edges. The final stage is to remove unwanted objects from the obtained output image. If this proposed segmentation is utilized as part of the CAD, the experts will be benefited for localizing the IVD and to diagnose the IVD disease.
机译:众所周知,图像分割在将数字图像划分为几个段。最近几天人类增加了腰部疼痛,因此木材脊柱病理检测成为计算机辅助诊断(CAD)系统中的主要研究区域。在腰椎病理学检测的过程中,椎间盘(IVD)的分割是主要的步骤,因为它识别体外诊断或体外诊断正常或在图像异常的边界。当轴向或腰椎MR图像的轴向或矢状图作为输入给出时,该建议的工作区段在轴向和矢状的视图中的IVD。 IVD的分割是一个四阶段过程。首先,对MR图像执行期望 - 最大化(EM)分割。 EM分段与群体大小的k均值产生优势。第二阶段是执行形态运算符和第三,应用边缘检测方法并获得边缘。最后阶段是从所获得的输出图像中删除不需要的对象。如果该拟议的分割作为CAD的一部分,专家将受益于本IVD本地化并诊断IVD疾病。

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