Segmentation as an effective method of isolating a brain tumor on MRI

I. Yurchuk, O. Kolesnyk
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Abstract

Digital image processing, which ensues in many sides of life, is one of the areas that requires rapid development and improvement of existing algorithms, both for accuracy and completeness, and for reasons of speed and cost-effectiveness of both technical and software solutions. Medical application itself is the area where both precision in processing is important, as insufficient information affects the treatment protocol, and the cost for availability and widespread use. In this research, an algorithm for segmentation of digital MRI images of the brain is proposed in order to isolate the segment that contains the tumor. This algorithm is based on the sequential execution of the following steps: threshold Otsu’s method of binarization of the image, selection of brain and tumor tissues by morphological operations, segmentation by marked watershed, removal of the skull line and selection of the segment containing the tumor by an erosion. The verification did not reveal false-positive segmentation results, and the percentage of images correctly segmented to detect the tumor was 96.2%. It should be noted the high speed of the segmentation process obtained by the authors.
分割是MRI分离脑肿瘤的一种有效方法
数字图像处理,随之而来的生活的许多方面,是一个需要快速发展和改进现有算法的领域之一,既是为了准确性和完整性,也是为了技术和软件解决方案的速度和成本效益。医疗应用本身就是一个处理精度很重要的领域,因为信息不足会影响治疗方案,而且获得和广泛使用的成本也很重要。在这项研究中,提出了一种分割算法的数字MRI图像的大脑,以分离包含肿瘤的部分。该算法基于以下步骤的顺序执行:阈值Otsu的图像二值化方法,通过形态学操作选择脑和肿瘤组织,通过标记分水岭分割,去除颅骨线,通过侵蚀选择包含肿瘤的部分。验证没有出现假阳性的分割结果,正确分割的图像检测到肿瘤的比例为96.2%。值得注意的是,作者获得的分割过程速度很快。
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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