Computationally efficient LC-SCS deep learning model for breast cancer classification using thermal imaging
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00521-024-09968-5.pdf
Reference46 articles.
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3. Moghbel M, Ooi CY, Ismail N, Hau YW, Memari N (2020) A review of breast boundary and pectoral muscle segmentation methods in computer-aided detection/diagnosis of breast mammography. Artif Intell Rev 53:1873–1918. https://doi.org/10.1007/s10462-019-09721-8
4. Nissar I, Alam S, Masood S, Kashif M (2024) MOB-CBAM: a dual-channel attention-based deep learning generalizable model for breast cancer molecular subtypes prediction using mammograms. Comput Methods Programs Biomed 248:108121. https://doi.org/10.1016/j.cmpb.2024.108121
5. Domingues I, Pereira G, Martins P, Duarte H, Santos J, Abreu PH (2020) Using deep learning techniques in medical imaging: a systematic review of applications on CT and PET. Artif Intell Rev 53:4093–4160. https://doi.org/10.1007/s10462-019-09788-3
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