Latest AI and machine learning research in radiology for healthcare professionals.
Dynamic magnetic resonance imaging (MRI) requires accurate reconstruction from undersampled k-space data to achieve high temporal resolution within clinically acceptable scan times. Deep unrolling architectures have recently emerged as effective solutions by integrating physics-based data consistency with learned priors. However, their ability to exploit temporal relationships remains limited, as ...
INTRODUCTION: High-resolution peripheral quantitative computed tomography (HR-pQCT) provides detailed bone microarchitecture assessments, but the interpretability of its many complex parameters remains challenging. This study aimed to develop a deep learning model to estimate skeletal age from HR-pQCT scans, offering an interpretable, quantitative summary of bone health relative to chronological a...
PURPOSE: To evaluate the measurement variability and reproducibility of prone imaging with quantitative computed tomography (QCT) compared with supine...
PURPOSES: To evaluate the diagnostic confidence in cerebral aneurysm embolization coil follow-up using the deep learning image reconstruction (DLIR) b...
PurposeThis study aimed to develop a reproducible manual segmentation method using a computer-assisted technique and to (1) compare extraocular muscle...
BACKGROUND AND OBJECTIVES: Use of companion robot pets to reduce social isolation and loneliness in older people is well-established. Outcomes associa...
Endometrial cancer represents a major global health concern, with rising incidence particularly in developed countries despite declining mortality rat...
BACKGROUND: Hypertension is a major contributor to cardiovascular morbidity and mortality. Its heterogeneity complicates risk stratification. Unsuperv...
Electrical Impedance Tomography (EIT) is a promising noninvasive imaging technique that reconstructs the spatial conductivity distribution from bounda...
Stroke remains a leading cause of mortality and long-term disability worldwide, where rapid diagnosis and timely intervention are critical for improvi...
BACKGROUND: Diagnosis of prostate cancer in the PSA gray zone (4-10Â ng/mL) and PI-RADS 3 cases remains challenging. Although multiparametric MRI (mpMR...
Artificial intelligence (AI) revolutionizes dentistry, enhancing diagnostic accuracy, treatment planning, and collaboration. This article examines AI'...
Magnetic resonance imaging (MRI) is an essential examination for ovarian cancer, in which ovarian tumor segmentation is crucial for personalized diagn...
Precision medicine has transformed healthcare by tailoring treatment plans to an individual's genetic profile, in contrast to standardized therapies. ...
Artificial intelligence (AI) has emerged as a transformative tool in liver imaging, offering enhanced diagnostic accuracy, efficiency, and reproducibi...
PURPOSE: To establish a comparability-first cine-MRI paradigm for small intestinal motility using a unified, feature-agnostic normalized differential ...
INTRODUCTION: Optimizing the diagnostic approach to thyroid nodules remains a crucial challenge. Ultrasound-based risk stratification systems such as ...
This editorial provides a concise overview of synthetic computed tomography (CT) generation from magnetic resonance imaging (MRI) for musculoskeletal ...
PURPOSE: Accurate identification of brain metastases is critical for determining prognosis and guiding treatment. Deep learning reconstruction (DLR) e...
PURPOSE OF REVIEW: To review contemporary applications, performance, and implementation challenges of artificial intelligence (AI) in the radiological...