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Slice specific atlas independent hippocampus segmentation using simple labeling

机译:使用简单标签对特定的图谱独立的海马区域进行分割

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摘要

Identification of objects of interest is most sought problem in computer vision related applications. This is in particular needed, when large volumes of data are available and a decision is to be made regarding relevance of an object to a specific region. In medical related applications, analysis of structural variations is much required for disease identification and progression. Manually delineating the affected portions is time consuming and prone to error. In the current paper, a novel algorithm is proposed to extract most significant tissue of human brain, Hippocampus. The algorithm uses labeling algorithm which is simple of its kind and does not need any prior knowledge. The segmented results are further compared with ground truth image using most prominent similarity indices, Dice Similarity Coefficient (DSC) and Jaccard coefficient.
机译:在计算机视觉相关应用中,最感兴趣的问题是识别感兴趣的对象。当可获得大量数据并要确定对象与特定区域的相关性时,尤其需要这样做。在医学相关应用中,非常需要对结构变异进行分析才能确定疾病和进展。手动划定受影响的部分非常耗时且容易出错。在当前的论文中,提出了一种新颖的算法来提取人脑最重要的组织海马体。该算法使用简单的标记算法,不需要任何先验知识。使用最突出的相似性指标,骰子相似性系数(DSC)和Jaccard系数,将分割结果与地面真实图像进行进一步比较。

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