Diagnostic performance of the deep learning method trained using MRI and F-18 FDG-PET/CT images in the evaluation of axillary lymph node metastasis in breast cancer patients
The deep learning model demonstrated promising diagnostic capability for noninvasively detecting ALNM. While not yet a replacement for SLNB, such models may assist clinical decision-making and reduce the need for invasive procedures in the future.
Authors
- Yeliz Cavus
- Aygül Polat Kelle (ORCID: https://orcid.org/0000-0001-6966-5826)
- Adnan Kuvvetli (ORCID: https://orcid.org/0000-0002-0725-6629)
- Mehmet Sarıgül (ORCID: https://orcid.org/0000-0001-7323-6864)
- Barış Ata (ORCID: https://orcid.org/0009-0001-4793-4607)
- Yahya Selcuk Aydede
- Abdullah Ilbey Yetim
- Umit Turan
Institutions
- Sağlık Bilimleri Üniversitesi (TR)
- Cukurova University (TR)
Publication Details
- Journal
- Journal of Cancer Research and Therapeutics
- Published
- 2025-10-01
- DOI
- https://doi.org/10.4103/jcrt.jcrt_493_25
- Primary Topic
- Breast Cancer Treatment Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00