文章基本信息

标题：Novel Seed Selection and Conceptual Region Growing Framework for Medical Image Segmentation
其他标题：Novel Seed Selection and Conceptual Region Growing Framework for Medical Image Segmentation
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作者：Humera Tariq ; Tahseen Jilani ; Usman Amjad 等
期刊名称：Brain. Broad Research in Artificial Intelligence and Neuroscience
印刷版ISSN：2067-3957
出版年度：2019
卷号：10
期号：1
页码：6-19
出版社：EduSoft publishing
摘要：The objective of the paper is to propose a novel idea to improve initial conditions of seeded region growing (SRG) algorithm. We also propose a conceptual region growing framework to contribute to its progress in medical imaging. Our scheme is based on the simple observation that nature seems random but it repeats itself. Medical images are a kind of natural images and hence they must have a tendency of behaving like fractals. Our non-parametric Polygonal Seed Selection method does not need density estimation as before and shows clear Improvement to handle over segmentation problem. Qualitative results have been demonstrated on Axial Slices of Brain using traditional SRG, K-Means and Watershed segmentation.
关键词：Region growing;K-Means;Watershed image segmentation;Brain Axial Slices