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 …

In the era of personalized medicine, the emphasis of health care is shifting from populations
to individuals. Artificial intelligence (AI) is capable of learning without explicit instruction and …

Background Although artificial intelligence (AI) shows promise across many aspects of
radiology, the use of AI to create differential diagnoses for rare and common diseases at …

Deep-learning methods for auto-segmenting brain images either segment one slice of the
image (2D), five consecutive slices of the image (2.5 D), or an entire volume of the image …

Purpose To develop and validate a neural network for automated detection and
segmentation of intracranial metastases on brain MRI studies obtained for stereotactic …

Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of
stroke survivors would be a useful aid in patient diagnosis and treatment planning. It would …

Neural networks were trained for segmentation and longitudinal assessment of
posttreatment diffuse glioma. A retrospective cohort (from January 2018 to December 2019) …

Purpose To assess how well a brain MRI lesion segmentation algorithm trained at one
institution performed at another institution, and to assess the effect of multi-institutional …

Body weight is an indispensable parameter for determination of contrast medium dose,
appropriate drug dosing, or management of radiation dose. However, we cannot always …

Globally, neurologic and mental disorders affect 1 in 3 people across their lifetime. 1
Uniquely positioned to improve imaging diagnosis and clinical management for patients with …