Head and neck tumors (HNTs) constitute a multifaceted ensemble of pathologies that
primarily involve regions such as the oral cavity, pharynx, and nasal cavity. The intricate …

Deep learning algorithms have demonstrated remarkable efficacy in various medical image
analysis (MedIA) applications. However, recent research highlights a performance disparity …

Objective. Deep learning shows promise in autosegmentation of head and neck cancer
(HNC) primary tumours (GTV-T) and nodal metastases (GTV-N). However, errors such as …

Early survival prediction is vital for the clinical management of cancer patients, as tumors
can be better controlled with personalized treatment planning. Traditional survival prediction …

Background. Head and neck cancer (HNC) is the seventh most common neoplastic disorder
at the global level. Contouring HNC lesions on [18 F] Fluorodeoxyglucose positron emission …

Deep learning (DL)-based methods have achieved state-of-the-art performance for a wide
range of medical image segmentation tasks. Nevertheless, recent studies show that deep …

Highlights What are the main findings? This multicenter retrospective study, encompassing
two hospital sites for training and leveraging data from forty-seven different hospitals for …

Simple Summary Artificial intelligence (AI) based on deep neural networks (DNNs) has
demonstrated great performance in computer vision. However, their clinical application in …

Routine computed tomography (CT) scans often detect a wide range of renal cysts, some of
which may be malignant. Early and precise localization of these cysts can significantly aid …

In the field of medical imaging, computed tomography (CT) scans have become crucial for
the detection and management of anatomical abnormalities. This study presents an …