Achieving high resolution while minimizing contrast agent dosage remains a key goal, yet a major challenge in contrast-enhanced computed tomography (CT) imaging. Herein, we propose an artificial intelligence-assisted low-dose high atomic number contr...
BACKGROUND: Accurate prediction of prognosis and risk stratification in patients with laryngeal cancer can inform appropriate treatment decision-making. This study aims to develop a multi-channel deep learning radiomics model based on contrast-enhanc...
PURPOSE: Segmentation of breast lesions in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is critical for effective diagnosis. This study investigates the impact of breast region segmentation (BRS) on the performance of deep learning-...
Late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) imaging plays a crucial role in assessing myocardial scar tissues, aiding in the diagnosis and prognosis of cardiovascular diseases. However, accurately classifying scar tissue severity...
BACKGROUND: Maximum intensity projections (MIPs) facilitate rapid lesion detection both for contrast-enhanced (CE) and diffusion-weighted imaging (DWI) breast magnetic resonance imaging (MRI). We evaluated the feasibility of AI-based virtual CE subtr...
Pharmacokinetic (PK) parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provide quantitative characterization of tissue perfusion and permeability. However, existing deep learning methods for PK parameter estimatio...
Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
Sep 27, 2025
PURPOSE: Tumors are heterogeneous and consist of subregions, also known as tumor habitats, each of which corresponds to a group of tissues with similar structural, metabolic or functional characteristics. This study aims to visualize and quantify int...
BACKGROUND: We aimed to quantify hepatic vessel volumes across chronic liver disease stages and healthy controls using deep learning-based magnetic resonance imaging (MRI) analysis, and assess correlations with biomarkers for liver (dys)function and ...
Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common cause of chronic liver disease worldwide, affecting over 30% of the global general population. Its progressive nature and association with other chronic diseases make...
PURPOSE: To develop and validate a hybrid radiomics model to predict the overall survival in pancreatic cancer patients and identify risk factors that affect patient prognosis.
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