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Survey of Modern Image Segmentation Algorithms on CT Scans of Hydrocephalic Brains

机译:脑积水CT扫描中现代图像分割算法的研究

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Paper presents the concept of applying image segmentation algorithms for precise extraction of cerebrospinal fluid (CSF) from CT brain scans. Accurate segmentation of the CSF from the intracranial brain area is crucial for further reliable analysis and quantitative assessment of hydrocephalus. Presented research was aimed at the comparison of effectiveness of three modern segmentation approaches used for this purpose. Specifically, random walk, level set and min-cut/max-flow algorithms were considered. The visual and numerical comparison of the segmentation results leads to conclusion that the most effective algorithm for the considered problem is level set, although the positive medical verification of the results revealed that either of considered algorithms can be successfully applied in the diagnostic applications.
机译:论文提出了应用图像分割算法从CT脑扫描中精确提取脑脊液(CSF)的概念。从颅内脑区域准确分割脑脊液对于进一步可靠地分析和定量评估脑积水至关重要。当前的研究旨在比较用于此目的的三种现代分割方法的有效性。具体而言,考虑了随机行走,水平集和最小切割/最大流量算法。分割结果的视觉和数值比较得出结论,即对所考虑问题的最有效算法是水平集,尽管对结果的积极医学验证表明,上述两种算法中的任何一种都可以成功地应用于诊断应用。

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