3d-cnn based computer-aided diagnosis (cadx) for lung nodule diagnosis

Tzu Chi Tai, Miao Tian, Wei-Ting Cho, Chin Feng Lai

研究成果: Conference contribution

摘要

For the lung nodule screening, one of the commonly testing methods is the chest radiograph. However, it is difficult to judge with the naked eye with the initial nodule size is usually less than one centimeter. It is known that skilled pulmonary radiologists have a high degree of accuracy in diagnosis, but there remain problems in disease diagnosis. These problems include the miss rate for diagnosis of small nodules and the diagnosis of change in preexisting interstitial lung disease. The recent studies have found that 68% lung cancer nodules in radiographs can be detected by one reader and 82% by two readers. In order to solve this problem, we proposed a 3D-CNN predicting model to differ malignant nodules from all nodules in computed tomography scan. In the experiment results, the model was able to achieve a training accuracy of 100% and a testing accuracy of 94.52%. It shows the proposed model is able to be used for improving the accuracy of detecting nodules.

原文English
主出版物標題Cognitive Cities - 2nd International Conference, IC3 2019, Revised Selected Papers
編輯Jian Shen, Yao-Chung Chang, Yu-Sheng Su, Hiroaki Ogata
發行者Springer
頁面35-43
頁數9
ISBN(列印)9789811561122
DOIs
出版狀態Published - 2020
事件2nd International Cognitive Cities Conference, IC3 2019 - Kyoto, Japan
持續時間: 2019 九月 32019 九月 6

出版系列

名字Communications in Computer and Information Science
1227 CCIS
ISSN(列印)1865-0929
ISSN(電子)1865-0937

Conference

Conference2nd International Cognitive Cities Conference, IC3 2019
國家Japan
城市Kyoto
期間19-09-0319-09-06

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

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