基于深度学习的肺结节分类

Q4 Engineering

Transactions of Japanese Society for Medical and Biological Engineering Pub Date : 2017-05-03 DOI:10.11239/JSMBE.55ANNUAL.516

Tomoki Kwajiri, Taro Tezuka

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引用次数: 4

摘要

将卷积神经网络(Convolutional Neural Network)、残差网络(Residual Network)等深度学习方法应用于CT扫描图像，对肺结节是否癌变进行分类。特别是，改变残差网络的层数所产生的影响。使用具有这两种网络结构的不同层数和参数的模型进行了实验。

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Classification of Lung Nodules Using Deep Learning

Deep learning methods such as the Convolutional Neural Network and the Residual Network were applied to CT scan images in order to classify whether lung nodules become cancerous or not. Especially, the effect of changing the number of layers in the Residual Network was. Experiment were carried out using several models having these two network architectures and consisting of different numbers of layers and parameters.

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来源期刊

Transactions of Japanese Society for Medical and Biological Engineering Engineering-Biomedical Engineering

CiteScore

0.10

自引率

0.00%

发文量