基于GLCM和反向传播神经网络的脑肿瘤智能分类系统

B. Jabber, K. Rajesh, D. Haritha, C. Z. Basha, Syed Nazia Parveen
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引用次数: 11

摘要

目前,医学领域的技术已经取得了很大的进步。可用于捕获大脑图像的方式有磁共振成像(mri)、正电子发射断层扫描(PET)和计算机断层扫描(CT)。其中,MR是与大脑解剖有关的最常用的判断工具。早期对肿瘤进行分类是避免脑肿瘤死亡的重要依据。提出了使用MRI对肿瘤进行计算机分类,其中使用灰度共生矩阵(GLCM)提取特征并使用BPNN进行分类。该方法的准确率达到94%。
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An Intelligent System for Classification of Brain Tumours With GLCM and Back Propagation Neural Network
Currently, technology has shown a lot of advancement in the field of medicine. Modalities available for capturing the brain images are Magnetic Resonance Imaging (MRIs), Positron Emission Tomography (PET) scan, and Computed Tomography (CT) scan. Among these MR is the most significantly used tool for judgment related to the anatomy of the brain. It is very essential for the classification of tumors in early-stage which supports avoiding the deaths due to brain tumors. Computerized classification of the tumor using MRI is proposed where features are extracted using the Gray Level Co-occurrence Matrices (GLCM) and classification using the BPNN. An accuracy of 94% is achieved with the proposed methodology.
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