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An interpretable deep hierarchical semantic convolutional neural network for lung nodule malignancy classification

机译：一种可解释的深层分层语义卷积神经网络，用于肺结节恶性分类

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Shiwen Shen; Simon X Han; Denise R Aberle; Alex A Bui; William Hsu;
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年度 2019
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1. An interpretable deep hierarchical semantic convolutional neural network for lung nodule malignancy classification [J] . Shen Shiwen, Han Simon X., Aberle Denise R., Expert Systems with Application . 2019,第AUGa期

机译：用于肺结节恶性分类的可解释的深层次语义卷积神经网络
2. An interpretable deep hierarchical semantic convolutional neural network for lung nodule malignancy classification [J] . Shen Shiwen, Han Simon X., Aberle Denise R., Expert systems with applications . 2019,第Auga期

机译：一种可解释的深层分层语义卷积神经网络，用于肺结节恶性分类
3. Integration of convolutional neural networks for pulmonary nodule malignancy assessment in a lung cancer classification pipeline [J] . Bonavita Ilaria, Rafael-Palou Xavier, Ceresa Mario, Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice . 2020,第期

机译：肺结结性肺结结性恶性评估的卷积神经网络整合肺癌分类管道
4. Classification of Lung Nodule Malignancy Risk on Computed Tomography Images Using Convolutional Neural Network: A Comparison Between 2D and 3D Strategies [C] . Xingjian Yan, Jianing Pang, Hang Qi, Asian conference on computer vision;Workshop on new trends in image restoration and enhancement;Workshop on assistive vision;ACCV workshop on hyperspectral image and signal processing;Workshop on computer vision technologies for smart vehicle;Workshop on spontaneous facial behavior analysis;Workshop on 3D modelling and applications;ACCV workshop on e-heritage;Workshop on multiview lip-reading challenges;Workshop on facial informatics;Workshop on discrete geometry and mathematical morphology for computer vision;Workshop on mathematical and computational methods in biomedical imaging and image analysis;International workshop on driver drowsiness detection from video;Workshop on meeting HCI with CV;Workshop on human identification for surveillance methods and applications;Workshop on benchmark and evaluation of surveillance task;Workshop on computer vision for affective computing;Workshop on interpretation and visualization of deep neural nets . 2017

机译：使用卷积神经网络对计算机断层扫描图像上的肺结节恶性风险进行分类：2D和3D策略之间的比较
5. Lung Nodule Classification Using Convolutional Neural Networks [D] . Wei, Qiushi. 2019

机译：肺结结使用卷积神经网络分类
6. Computer-aided diagnosis of lung nodule classification between benign nodule primary lung cancer and metastatic lung cancer at different image size using deep convolutional neural network with transfer learning [O] . Mizuho Nishio, Osamu Sugiyama, Masahiro Yakami, -1

机译：使用转移学习的深度卷积神经网络对不同图像大小的良性结节原发性肺癌和转移性肺癌之间的计算机辅助诊断
7. Computer-aided diagnosis of lung nodule classification between benign nodule, primary lung cancer, and metastatic lung cancer at different image size using deep convolutional neural network with transfer learning [O] . Mizuho Nishio, Osamu Sugiyama, Masahiro Yakami, 2018

机译：计算机辅助诊断良性结节，原发性肺癌和转移肺癌在不同图像大小与转移学习的不同图像尺寸

An interpretable deep hierarchical semantic convolutional neural network for lung nodule malignancy classification

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