Automatic Diagnose of Drug-Resistance Tuberculosis from CT Images Based on Deep Neural Networks

Author:

Du Qiuyu,Liang Shufan,Guo Jixiang,Yi Zhang,Li Weiming,Wang Chengdi,Xu Xiuyuan

Publisher

Springer Nature Switzerland

Reference26 articles.

1. Aghajanzadeh, E., Shomali, B., Aminshahidi, D., Ghassemi, N.: Classification of tuberculosis type on CT scans of lungs using a fusion of 2d and 3d deep convolutional neural networks. In: CLEF (Working Notes), pp. 1133–1144 (2021)

2. Ahmed, M.S., Sk, O., Jayatilake, M., Gonçalves, T., Rato, L.: Texture analysis from 3d model and individual slice extraction for tuberculosis MDR detection, type classification and severity scoring (2018)

3. Cha, J., et al.: Radiological findings of extensively drug-resistant pulmonary tuberculosis in non-aids adults: comparisons with findings of multidrug-resistant and drug-sensitive tuberculosis. Korean J. Radiol. 10(3), 207–216 (2009)

4. Chen, S., Guo, J., Wang, C., Xu, X., Yi, Z., Li, W.: DeepLNAnno: a web-based lung nodules annotating system for CT images. J. Med. Syst. 43(7), 1–9 (2019). https://doi.org/10.1007/s10916-019-1258-9

5. Cui, E.N., et al.: Radiomics model for distinguishing tuberculosis and lung cancer on computed tomography scans. World J. Clin. Cases 8(21), 5203 (2020)

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