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

S. Ren, Jun Wang, Zhongqiu Wang
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引用次数: 0

摘要

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