Interactive Segmentation of Capsule Endoscopy Images Using Grow Cut Method

P. Shanmugasundaram, N. Santhiyakumari
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引用次数: 3

Abstract

High incidence of Gastrointestinal (GI) tract related diseases are common nowadays, which leads to cancer. Diagnose of these kind of diseases is not easy in the early stage. This makes the researchers to develop an automated screening technique for early detection, many modalities are employed to view the GI tract but complete visualization is not possible. Wireless Capsule Endo scopy (WCE) is a modern modality which helps to view the complete GI tract, This claims an computational assistances which automatically segment the defective frames with the help of computer assisted diagnosis, In this paper the author describes an semi-automated interactive grow cut algorithm for segmenting capsule endoscopy (CE) images as foreground and background image by iterative process with a small number of user-labeled pixel the rest of the images are segmented with less human input. User can view and guide the algorithm without any additional user effort a semi automated segmentation is computed using mat lab.
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基于生长切口法的胶囊内窥镜图像交互式分割
目前,胃肠道相关疾病的高发是常见的,并导致癌症的发生。这类疾病的早期诊断并不容易。这使得研究人员开发了一种用于早期检测的自动筛查技术,许多方法被用来观察胃肠道,但完全可视化是不可能的。无线胶囊内镜(WCE)是一种现代模式,有助于查看完整的胃肠道,这要求一个计算辅助,在计算机辅助诊断的帮助下自动分割缺陷框架。本文描述了一种半自动化交互式生长切割算法,该算法通过迭代处理将胶囊内窥镜(CE)图像分割为前景和背景图像,使用少量用户标记的像素,其余图像以较少的人工输入进行分割。用户可以查看和指导算法,而无需任何额外的用户努力,使用mat lab计算半自动分割。
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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