Latest AI and machine learning research in radiology for healthcare professionals.
Medical image classification (IC) is a method for categorizing images according to the appropriate p...
BACKGROUND: CD8+ T lymphocyte infiltration is closely associated with the prognosis and immunotherap...
BACKGROUND: Reduced bone density is recognized as a predictor for potential complications in reverse...
Magnetic resonance-guided focused ultrasound surgery (MRgFUS) thalamotomy is an emerging technique f...
Intracranial vessel wall imaging (VWI), which requires both high spatial resolution and high signal-...
This study aimed to establish and validate the efficacy of a nomogram model, synthesized through the...
This study aimed to compare the image quality and detection performance of pancreatic cystic lesions...
Ultrasound images are susceptible to various forms of quality degradation that negatively impact dia...
Artificial intelligence (AI) is becoming increasingly integral in clinical practice, such as during ...
BACKGROUND: Cerebral small vessel disease is the most common pathology underlying vascular dementia....
Diagnosing liver lesions is crucial for treatment choices and patient outcomes. This study develops ...
BACKGROUND:  The early diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI) rem...
OBJECTIVES: This study investigated patients' acceptance of artificial intelligence (AI) for diagnos...
For conditions like osteoporosis, changes in bone pore geometry even when porosity is constant have ...
OBJECTIVE: Myocardial contrast echocardiography (MCE) plays a crucial role in diagnosing ischemia, i...
PURPOSE: Develop a universal lesion recognition algorithm for PET/CT and PET/MRI, validate it, and e...
BACKGROUND: Fluoroscopy guided interventions (FGIs) pose a risk of prolonged radiation exposure; per...
Innovative intraoral ultrasound devices with smart artificial intelligence-based identification for ...
To investigate whether peritumoral edema (PE) could enhance deep learning radiomic (DLR) model in pr...
This study investigated the usefulness of deep learning-based automatic detection of temporomandibul...
To develop a deep learning-based model capable of segmenting the left ventricular (LV) myocardium on...