Pulmonary Nodule Detection and False Acceptance Reduction: Review-Reference-Cited by-同舟云学术

Pulmonary Nodule Detection and False Acceptance Reduction: Review

Published:2020-08-30 Issue: Volume: Page:605-612
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
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Author:

Pawar Sheetal,Patil Babasaheb

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-5679-1_58

Reference22 articles.

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2. Talukdar, J., Sarma, P.: An approach to classify lung nodules for detection of cancer cells. In: 5th International Conference on Advanced Computing and Communication Systems (ICACCS), pp. 189–192. Coimbatore, India (2019). https://doi.org/10.1109/icaccs.2019.8728332

3. Rahman, M.S., Shill, P.C., Homayra, Z.: A new method for lung nodule detection using deep neural networks for CT images. In: International Conference on Electrical, Computer and Communication Engineering (ECCE), pp. 1–6. Cox’sBazar, Bangladesh (2019). https://doi.org/10.1109/ecace.2019.8679439

4. Nadkarni, N.S., Borkar, S.: Detection of lung cancer in CT Images using image processing. In: 3rd International Conference on Trends in Electronics and Informatics (ICOEI), pp. 863–866. Tirunelveli, India (2019). https://doi.org/10.1109/icoei.2019.8862577

5. Makaju, S., Prasad, P.W.C., Alsadoona, A., Singhb, A.K., Elchouemi, A.: Lung cancer detection using CT scans. In: 6th International Conference on Smart Computing and Communications ICSCC. Procedia Computer Science 125, pp. 107–114. Sciencedirect, Kurukshetra, India (2017). https://doi.org/10.1016/j.procs.2017.12.016