Deep learning–based classification of parotid gland tumors: integrating dynamic contrast-enhanced MRI for enhanced diagnostic accuracy
Adding DCE-MRI data to deep learning models substantially enhances parotid gland tumor classification accuracy, highlighting the value of functional imaging biomarkers in improving noninvasive diagnostic workflows.
Authors
- İlker Özgür Koska (ORCID: https://orcid.org/0000-0003-0971-3827)
- Nüket Eliyatkın (ORCID: https://orcid.org/0000-0002-7784-5699)
- Kazım Ayberk Sinci (ORCID: https://orcid.org/0000-0002-2207-5850)
- Büşra Candan (ORCID: https://orcid.org/0000-0002-5138-5583)
- Ali Murat Koç (ORCID: https://orcid.org/0000-0001-6824-4990)
- Yusuf Kenan Çetinoğlu (ORCID: https://orcid.org/0000-0002-7878-6117)
- Çağan Koska (ORCID: https://orcid.org/0000-0003-0484-5046)
- Nezahat Erdoğan (ORCID: https://orcid.org/0000-0003-0939-5080)
Institutions
- Dokuz Eylül University (TR)
- Izmir Kâtip Çelebi University (TR)
- Dr. Behçet Uz Çocuk Hastalıkları Hastanesi (TR)
- İstanbul Kanuni Sultan Süleyman Eğitim ve Araştırma Hastanesi (TR)
- Yaşar University (TR)
Publication Details
- Journal
- BMC Medical Imaging
- Published
- 2025-07-04
- DOI
- https://doi.org/10.1186/s12880-025-01814-x
- Citations
- 4
- Primary Topic
- Salivary Gland Tumors Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 8.03