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Deep Convolutional Neural Network for the Classification of Hepatocellular Carcinoma and Intrahepatic Cholangio carcinoma

机译:肝细胞癌分类和肝内胆管癌的深度卷积神经网络

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Liver cancer is the second leading cause of cancer-related death worldwide.~1 Hepatocellular carcinoma (HCC) is the most common primary liver cancer accounting for approximately 80% of cases. Intrahepatic cholangiocarci-noma (ICC) is a rare liver cancer, arising in patients with the same risk factors as HCC, but treatment options and prognosis differ. The diagnosis of HCC is based primarily on imaging but distinguishing between HCC and ICC is challenging due to common radiographic features.~(2-4) The aim of the present study is to classify HCC and ICC in portal venous phase CT. 107 patients with resected ICC and 116 patients with resected HCC were included in our analysis. We developed a deep neural network by modifying a pre-trained Inception network by retraining the final layers. The proposed method achieved the best accuracy and area under the receiver operating characteristics curve of 69.70% and 0.72, respectively on the test data.
机译:肝癌是全世界癌症相关死亡的第二个主要原因。〜1肝细胞癌(HCC)是最常见的原发性肝癌占案件的约80%。肝脏胆囊胰腺癌(ICC)是一种罕见的肝癌,患有与HCC相同危险因素的患者,但治疗方案和预后不同。 HCC的诊断主要基于成像,但在常见的射线照相特征上,HCC和ICC之间的挑战是具有挑战性的。〜(2-4)本研究的目的是将HCC和ICC分类在门静脉期CT中。在我们的分析中包含107例被切除的ICC和116例切除HCC患者。我们通过再培训最终层来修改预先训练的初始网络来开发了深度神经网络。所提出的方法在测试数据中分别实现了69.70%和0.72的接收器操作特性曲线下的最佳精度和面积。

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