基于深度神经网络的脑肿瘤四级分类系统

Nimmy George, Manju Manuel
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引用次数: 2

摘要

神经胶质瘤是一种常见的原发性脑肿瘤,起源于神经胶质细胞。最常见的脑胶质瘤是发生在星形胶质细胞中的星形细胞瘤,星形胶质细胞被称为星形胶质细胞。星形细胞瘤的四级分类取决于肿瘤的生长速度和扩散速度。提出了一种将星形细胞瘤划分为四个等级的新方法。系统的性能评价基于敏感性、特异性、精密度、马修斯相关系数、准确度和FScore等统计指标。将MRI图像应用于支持向量机分类器,并对其性能进行比较。结果表明,该分类器的分类性能明显优于支持向量机等传统分类器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Four Grade Brain Tumor Classification System Using Deep Neural Network
One of the commonly found primary brain tumor is glioma which originate in glial cells. The most commonly found glioma brain tumor is astrocytoma that arises in astrocytes which are star shaped glial cells called astrocytes. The four grade classification of astrocytoma depends upon how fast the tumor grows and its spreading. A novel approach for classifying astrocytoma brain tumor into four grades is proposed. The performance evaluation of the system done is based on statistical measures such as sensitivity, specificity, precision, Mathews Correlation Coefficient, accuracy and FScore. The MRI images are also applied to a Support Vector Machine Classifier and performance is compared. It is found that the performance of the proposed system is very much better than conventional classifiers like SVM.
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