An Intelligent Diagnosis Method of MRI in Classifying Prostate Cancerous Tissue Using SVM Algorithm with Different Kernels

S. Ren, Jun Wang, Zhongqiu Wang
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Abstract

Prostate cancer (Pca) is the most common malignancy and the second most dominant cause of cancer-related deaths in men in Western countries, with an incidence rate composed over 200 per 100,000 men. 1 The early diagnosis of Pca will lead to an obvious increase of patients’ survival, and as a result, a decrease of treatment costs. 2 Rapid and accurate diagnosis of Pca is for (mp-MRI) anatomic with functional MRI technique, for diagnosis, of T2-weighted contributions to the localization and characterization of abnormalities in the T2WI are of identifying the
基于不同核向量机算法的MRI前列腺癌组织分类智能诊断方法
前列腺癌(Pca)是西方国家男性最常见的恶性肿瘤,也是癌症相关死亡的第二大主要原因,发病率超过200 / 100,000。1前列腺癌的早期诊断会明显提高患者的生存率,从而降低治疗费用。快速准确地诊断前列腺癌是为了(mp-MRI)解剖与功能MRI技术,对于诊断,t2加权贡献的定位和特征的异常在T2WI是识别
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