A feature engineering-based machine learning technique to detect and classify lung and colon cancer from histopathological images
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Biomedical Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11517-023-02984-y.pdf
Reference58 articles.
1. Adu K, Yu Y, Cai J et al (2021) DHS-CapsNet: dual horizontal squash capsule networks for lung and colon cancer classification from whole slide histopathological images. Int J Imaging Syst Technol 31:2075–2092. https://doi.org/10.1002/ima.22569
2. Mehmood S, Ghazal TM, Khan MA et al (2022) Malignancy detection in lung and colon histopathology images using transfer learning with class selective image processing. IEEE Access 10:25657–25668. https://doi.org/10.1109/ACCESS.2022.3150924
3. Lung Cancer Statistics | How common is lung cancer? https://www.cancer.org/cancer/lung-cancer/about/key-statistics.html. Accessed 11 Jan 2023
4. Attallah O, Aslan MF, Sabanci K (2022) A framework for lung and colon cancer diagnosis via lightweight deep learning models and transformation methods. Diagnostics 12:2926. https://doi.org/10.3390/diagnostics12122926
5. Kurishima K, Miyazaki K, Watanabe H et al (2017) Lung cancer patients with synchronous colon cancer. Mol Clin Oncol 8:137–140. https://doi.org/10.3892/mco.2017.1471
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Vision Transformer Based Effective Model for Early Detection and Classification of Lung Cancer;SN Computer Science;2024-08-29
2. Automated Lung and Colon Cancer Classification Using Histopathological Images;Biomedical Engineering and Computational Biology;2024-01
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