Tuberculosis detection using deep learning and contrast-enhanced canny edge detected X-Ray images

• 主要な著者: Kieu, Stefanus Tao Hwa, Abdullah Bade, Mohd Hanafi Ahmad Hijazi, Mohammad Saffree Jeffree
• フォーマット: 論文
• 言語: English; English
• 出版事項: Institute of Advanced Engineering and Science (IAES) 2020
• 主題: RC306-320.5 Tuberculosis
• オンライン･アクセス: https://eprints.ums.edu.my/id/eprint/30356/2/Tuberculosis%20detection%20using%20deep%20learning%20and%20contrast-enhanced%20canny%20edge%20detected%20X-Ray%20images%20ABSTRACT.pdf; https://eprints.ums.edu.my/id/eprint/30356/5/Tuberculosis%20detection%20using%20deep%20learning%20and%20contrast-enhanced%20canny%20edge%20detected%20X-Ray%20images%20FULL%20TEXT.pdf; https://eprints.ums.edu.my/id/eprint/30356/; https://www.researchgate.net/publication/348268058_Tuberculosis_detection_using_deep_learning_and_contrastenhanced_canny_edge_detected_X-Ray_images; https://doi.org/10.11591/ijai.v9.i4.pp713-720

Tuberculosis (TB) is a disease that causes death if not treated early. Ensemble deep learning can aid early TB detection. Previous work trained the ensemble classifiers on images with similar features only. An ensemble requires a diversity of errors to perform well, which is achieved using either di...