Segmentation and Classification of Lung Cancer using Deep Learning Techniques-Reference-Cited by-同舟云学术

Segmentation and Classification of Lung Cancer using Deep Learning Techniques

Published:2024 Issue: Volume:235 Page:3226-3235
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

Kanakaraddi Suvarna G,Handur Vidya S,Jalannavar Anjana,Chikaraddi Ashok,Giraddi Shantala

Publisher

Elsevier BV

Reference18 articles.

1. L. Zhong, G. Wang, X. Liao and S. Zhang, "HAMIL: High-resolution Activation Maps and Interleaved Learning for Weakly Supervised Segmentation of Histopathological Images," in IEEE Transactions on Medical Imaging, Doi: 10.1109/TMI.2023.3269798.

2. R. Tekade and K. Rajeswari, "Lung Cancer Detection and Classification Using Deep Learning," 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), Pune, India, 2018, pp. 1-5, Doi: 10.1109/ICCUBEA.2018.8697352.

3. “M. Sangeetha, R. M. Devi, H. Gunasekaran, R. Venkatesan, K. Ramalakshmi and P. Murugesan, "Deep Residual Learning for Lung Cancer Nodules Detection and Classification," 2023 7th International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, 2023, pp. 907-912, doi: 10.1109/ICCMC56507.2023.10083783.

4. Yilong Li, Zhaoyang Xu, YAQI WANG. “SUNet and DUNet Fusion for Tumor Segmentation in Histopathology Images” Published in: 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

5. J. Moranguinho, T. Pereira, B. Ramos, J. Morgado, J. L. Costa and H. P. Oliveira, "Attention Based Deep Multiple Instance Learning Approach for Lung Cancer Prediction using Histopathological Images," 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Mexico, 2021, pp. 2852-2855, doi: 10.1109/EMBC46164.2021.9631000.