基于深度学习网络的肺癌检测:比较分析

Susmita Das, Swanirbhar Majumder
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引用次数: 9

摘要

深度学习是一种新兴的、有影响力的特征学习和模式识别方法。本文对基于深度学习技术的计算机辅助诊断方案与传统的计算机辅助诊断方案进行了比较。在本文中,我们比较了几种用于肺癌识别的深度神经网络。在我们的研究中,我们发现与深度学习技术中的其他算法相比,卷积神经网络在大多数情况下用于肺癌检测。总之,我们解决了在肺癌诊断系统实施中的一些困难,然后总结了现有肺癌诊断算法的优点和缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lung Cancer Detection Using Deep Learning Network: A Comparative Analysis
Deep learning is an emergent and influential method which is used for feature learning and pattern recognition. We provide a comparison between Computer Aided Diagnosis scheme using Deep Learning Technique and traditional Computer Aided Diagnosis scheme in our paper. In this paper, we have compared several deep neural networks for recognition of pulmonary cancer. In our study, we find that Convolutional neural networks are used for pulmonary cancer detection in most of the cases, as compared to other algorithms in deep learning techniques. In conclusion, we address the few difficulties in the implementation of the systems for pulmonary cancer, then we summarise the advantages and disadvantages of the existing algorithms for diagnosis of pulmonary cancer.
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