基于直方图研究和支持向量机分类的肿瘤提取与检测方法

IF 0.6 Q3 Engineering
Sara Sandabad, A. Benba, Y. Tahri, A. Hammouch
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引用次数: 0

摘要

在本文中,我们提出了一种新的方法来检测和分割脑肿瘤区域加权脑MRI在T1(与对比)。该方法包括三个主要阶段:(i)使用EMBE方法提取感兴趣的区域(大脑);(ii)对MRI图像进行研究和直方图分析,以创建学习和初始化分类算法,稍后将应用于检索和定位肿瘤;(iii)利用支持向量机对肿瘤进行检测和分类,分为肿瘤类和无肿瘤类两类。我们的方法将通过确定其几何特性来完成肿瘤区域的表征。这项工作将有助于以后放射科医生每天处理大量MRI图像的巨大任务,也可能是未来研究人员开发其他新方法的一种方式,并使这项研究变得如此有趣。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel extraction and tumour detection method using histogram study and SVM classification
In this article we present a new method for detecting and segmenting brain tumour regions weighted brain MRI in T1 (with contrast). This method consists of three main stages: (i) extracting the region of interest (brain) using our EMBE method; (ii) study and histogram analysis of the MRI image to create learning and initialise the classification algorithm will be applied later to retrieve and locate the tumour; (iii) tumour detection and classification using SVM into two classes: tumour class and no-tumour class. Our method will be completed by a characterisation of the tumour area by determining its geometric properties. This work will facilitate later the immense task radiologists to the significant number of MRI images have to deal with daily, and may also be a way for future researchers in order to develop other new methods and develop this research so interesting.
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