Image Processing based Brain Tumor Detection

Shivam Varshney, Shubham Kumar Prajapati, Sahil Rajput, Mandeep Kaur, Nitin Rakesh, Mayank Kumar Goyal
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Abstract

The formation of abnormal cells within the brain is referred to as a "brain tumor." There are numerous types of brain tumors. Some of the brain tumors are cancer causing (Malignant) and others are non cancerous (benign). Magnetic resonance imaging (MRI) is a technology that is used to identify and classify brain cancers. After an MRI establishes the existence of a brain tumor, the most frequent method for determining the kind of tumor is to biopsy or operate on a sample of tumor tissue. Though the first process is done by a really experienced person as brain tumors are a very serious issue and need an experienced person to confirm that. In this whole process MRI can’t confirm about any tumor. It shows only the image of the internal image of brain tissue. Image processing is a very powerful tool to analyze MRI images with the help of different algorithms and using some other data. In this there are many parameters used to finalize whether there is tumor or not some of the parameters are accuracy. This paper discusses the many approaches and procedures used to identify brain cancers, as well as the accuracy of detecting the tumor in the brain using Image processing, which includes steps: Pre-processing, Segmentation, Threshold segmentation, Feature extraction, Classification using SVM (Support Vector Machine).
基于图像处理的脑肿瘤检测
大脑中异常细胞的形成被称为“脑瘤”。脑瘤有很多种类型。有些脑瘤是致癌的(恶性的),有些则是非癌性的(良性的)。磁共振成像(MRI)是一种用于识别和分类脑癌的技术。在核磁共振成像确定脑肿瘤存在后,确定肿瘤类型的最常用方法是对肿瘤组织样本进行活组织检查或手术。虽然第一个过程是由一个非常有经验的人完成的,因为脑瘤是一个非常严重的问题,需要一个有经验的人来确认。在整个过程中,MRI无法确认任何肿瘤。它只显示了脑组织的内部图像。图像处理是一个非常强大的工具,可以在不同算法的帮助下分析MRI图像,并使用一些其他数据。其中有许多参数用于确定是否有肿瘤,其中一些参数是准确的。本文讨论了用于脑癌识别的多种方法和程序,以及使用图像处理检测大脑肿瘤的准确性,包括预处理,分割,阈值分割,特征提取,支持向量机分类。
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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