Rata Rokhshad, Seyyede Niloufar Salehi, Amirmohammad Yavari, Parnian Shobeiri, Mahdieh Esmaeili, Nisha Manila, Saeed Reza Motamedian, Hossein Mohammad-Rahimi
PURPOSE: This study aims to review deep learning applications for detecting head and neck cancer (HNC) using magnetic resonance imaging (MRI) and radiographic data. METHODS: Through January 2023, a PubMed, Scopus, Embase, Google Scholar, IEEE, and arXiv search were carried out. The inclusion criteria were implementing head and neck medical images (computed tomography (CT), positron emission tomography (PET), MRI, Planar scans, and panoramic X-ray) of human subjects with segmentation, object detection, and classification deep learning models for head and neck cancers...
October 19, 2023: Oral Radiology