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A computer-aided approach for meningioma brain tumor detection using CANFIS classifier

机译:使用CANFIS分类器的计算机辅助脑膜瘤脑肿瘤检测方法

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摘要

Abnormal growth of cells in brain leads to the formation of tumors in brain. The earlier detection of the tumors in brain will save the life of the patients. Hence, this article proposes a computer-aided fully automatic methodology for brain tumor detection using Co-Active Adaptive Neuro Fuzzy Inference System (CANFIS) classifier. The internal region of the brain image is enhanced using image normalization technique and further contourlet transform is applied on the enhanced brain image for the decomposition with different scales. The grey level and heuristic features are extracted from the decomposed coefficients and these features are trained and classified using CANFIS classifier. The performance of the proposed brain tumor detection is analyzed in terms of classification accuracy, sensitivity, specificity, and segmentation accuracy.
机译:脑中细胞的异常生长导致脑中肿瘤的形成。尽早发现脑部肿瘤将挽救患者的生命。因此,本文提出了一种使用辅助自适应神经模糊推理系统(CANFIS)分类器进行脑肿瘤检测的计算机辅助全自动方法。使用图像归一化技术增强了大脑图像的内部区域,并在增强后的大脑图像上应用了进一步的轮廓波变换,以进行不同尺度的分解。从分解后的系数中提取灰度和启发式特征,并使用CANFIS分类器对这些特征进行训练和分类。从分类准确性,敏感性,特异性和分割准确性方面分析提出的脑肿瘤检测的性能。

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