基于深度学习的胰腺黏液性和浆液性囊性肿瘤的多源特征分类模型

徐真顺,袁小涵,黄子珩,邵成伟,武杰,边云

Multi-source Feature Classification Model of Pancreatic Mucinous and Serous Cystic Neoplasms Based on Deep Learning

XU Zhenshun,YUAN Xiaohan,HUANG Ziheng,SHAO Chengwei,WU Jie,BIAN Yun

图2 ResNet50提取深度学习特征过程，图中包含4个卷积块（Conv）、平均池化层（Av-pool）以及全连接层（fc）

Fig. 2 The process of ResNet50 extracting deep learning features, which includes four convolution blocks (Conv), average pooling layer (Av-pool) and fully connected layer (fc)