https://scholars.lib.ntu.edu.tw/handle/123456789/546597
標題: | Two-stage classification of tuberculosis culture diagnosis using convolutional neural network with transfer learning | 作者: | Chang, R.-I. Chiu, Y.-H. Lin, J.-W. RAY-I CHANG |
關鍵字: | Automatic tuberculosis diagnosis; Deep learning; Multi-stage classification; Transfer learning; Tuberculosis culture test | 公開日期: | 2020 | 卷: | 76 | 期: | 11 | 起(迄)頁: | 8641-8656 | 來源出版物: | Journal of Supercomputing | 摘要: | Tuberculosis (TB) has been one of top 10 leading causes of death. A computer-aided diagnosis system to accelerate TB diagnosis is crucial. In this paper, we apply convolutional neural network and deep learning to classify the images of TB culture test—the gold standard of TB diagnostic test. Since the dataset is small and imbalanced, a transfer learning approach is applied. Moreover, as the recall of non-negative class is an important metric for this application, we propose a two-stage classification method to boost the results. The experiment results on a real dataset of TB culture test (1727 samples with 16,503 images from Tao-Yuan General Hospital, Taiwan) show that the proposed method can achieve 99% precision and 98% recall on the non-negative class. ? 2020, Springer Science+Business Media, LLC, part of Springer Nature. |
URI: | https://www.scopus.com/inward/record.url?eid=2-s2.0-85078622025&partnerID=40&md5=ce99067d3aaf2e563025fb1aa8162d11 https://scholars.lib.ntu.edu.tw/handle/123456789/546597 |
DOI: | 10.1007/s11227-020-03152-x | SDG/關鍵字: | Convolution; Deep learning; Neural networks; Statistical tests; Classification methods; Computer aided diagnosis systems; Convolutional neural network; Diagnostic tests; General hospitals; Multi stage; Transfer learning; Tuberculosis diagnosis; Computer aided diagnosis |
顯示於: | 工程科學及海洋工程學系 |
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