Slice specific atlas independent hippocampus segmentation using simple labeling

G. Murthy, B. Anuradha, S. Krishna, B. Reddy, R. Sithara
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引用次数: 1

Abstract

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.
使用简单标记进行特异性图谱独立海马分割
感兴趣对象的识别是计算机视觉相关应用中最受关注的问题。当有大量可用的数据,并且要就对象与特定区域的相关性做出决定时,这是特别需要的。在医学相关应用中,对结构变异的分析对于疾病的识别和进展是非常必要的。手动描绘受影响的部分既耗时又容易出错。本文提出了一种提取人脑最重要组织海马的新算法。该算法采用标注算法,是同类算法中最简单的,不需要任何先验知识。利用最突出的相似度指标,Dice similarity Coefficient (DSC)和Jaccard系数,将分割结果与ground truth图像进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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