主动轮廓随机漫步器与分水岭算法在卵巢癌图像分割中的比较分析

P. J. Ruchitha, Richitha Y Sai, Ashwini Kodipalli, R. J. Martis, Santosh K. Dasar, Taha Ismail
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引用次数: 8

摘要

在最近的时代,图像处理已经成为医学科学领域最常用的领域之一,包括不同类型的程序,即提取,图像获取,检测,手术计划和展示,这确实有助于给病人提供有效的治疗,使用所有这些技术,疾病也可以在早期被发现。就卵巢癌而言,如果在早期发现,就可以成功治疗。根据以下统计数据,在开始阶段识别卵巢癌症是非常重要的。今天,有许多算法正在实施,以检测癌症,即通过分割。这是三种算法随机步行者,活动轮廓和分水岭正在实施,以分割卵巢癌。最后,进行了比较分析,以确定哪种算法在三种算法中给出了更好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative analysis of active contour random walker and watershed algorithms in segmentation of ovarian cancer
In the recent era, Image processing has been one of the most commonly used domain in the field of medical science that includes different kinds of procedures namely extraction, image gaining, detection, surgical planning and presentation which indeed helps in giving effective treatment to the patient and using all those techniques, the disease could also be detected at a early stage. When it comes to the case of ovarian cancer, it could be treated successfully when detected at an early stage.As per the following statistics, it is very much important to identify the cancer in the ovaries at the starting stage. Today, there are many algorithms that are being implemented in order to detect the cancer i.e. by segmentation. Here are the three algorithms Random Walker, Active Contour and Watershed that are being implemented in order to segment the ovarian cancer. Finally, a comparative analysis is being performed to identify which gives a better result among the three algorithms.
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