Brain Tumor Detection Using Wathershed Segmentation Techniques and Area Calculation

M. Pareek, C. Jha, S. Mukherjee, Chandani Joshi
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引用次数: 2

Abstract

This paper primarily focuses on to employ a novel approach to classify the brain tumor and its area. The Tumor is an uncontrolled enlargement of tissues in any portion of the human body. Tumors are of several types and have some different characteristics. According to their characteristics some of them are avoidable and some are unavoidable. Brain tumor is serious and life threatening issues now days, because of today’s hectic lifestyle. Medical imaging play important role to diagnose brain tumor .In this study an automated system has been proposed to detect and calculate the area of tumor. For proposed system the experiment carried out with 150 T1 weighted MRI images. The edge based segmentation, watershed segmentation has applied for tumor, and watershed segmentation has used to extract abnormal cells from the normal cells to get the tumor identification of involved and noninvolved areas so that the radiologist differentiate the affected area. The experiment result shows tumor extraction and area of tumor find the weather it is benign and malignant.
基于Wathershed分割技术和面积计算的脑肿瘤检测
本文主要探讨一种新的脑肿瘤及其区域分类方法。肿瘤是人体任何部位组织不受控制的扩大。肿瘤有几种类型,有一些不同的特征。根据他们的特点,有些是可以避免的,有些是不可避免的。由于当今繁忙的生活方式,脑瘤是一个严重的威胁生命的问题。医学影像在脑肿瘤诊断中发挥着重要的作用,本研究提出了一种用于脑肿瘤面积检测和计算的自动化系统。对于所提出的系统,实验使用150张T1加权MRI图像进行。将基于边缘的分割、分水岭分割应用于肿瘤,利用分水岭分割从正常细胞中提取异常细胞,得到受累和非受累区域的肿瘤识别,从而使放射科医师区分受累区域。实验结果表明,肿瘤的提取和肿瘤的面积可以判断肿瘤的良恶性。
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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