【24h】

Deep Learning for Categorization of Lung Cancer CT Images

机译:深度学习对肺癌CT图像进行分类

获取原文
获取原文并翻译 | 示例

摘要

Lung cancer is a serious health problem. In the United States alone, approximately 225,000 people each year are diagnosed with lung cancer. Early detection is a crucial part of giving patients the best chance of recovery. Deep learning gives us an opportunity to increase the accuracy of the automated initial diagnosis. Here we present an ensemble of Convolution Neural Networks(CNN) using multiple preprocessing methods to increase the accuracy of the automated labeling of the scans. We have done this by implementing ensembles of CNNs along with a voting system to get the consensus of the two networks. The initial results of our best method show both a consistently high accuracy (97.5%) and a low percentage of false positives (
机译:肺癌是一个严重的健康问题。仅在美国,每年约有225,000人被诊断出患有肺癌。尽早发现是为患者提供最佳康复机会的关键部分。深度学习使我们有机会提高自动化初始诊断的准确性。在这里,我们提出了使用多种预处理方法来提高卷积自动标记扫描准确性的卷积神经网络(CNN)的合奏。为此,我们通过实现CNN集成以及投票系统来实现这两个网络的共识。我们最好的方法的初步结果显示出始终如一的高精度(97.5%)和低的误报率(

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号