Latest AI and machine learning research in radiology for healthcare professionals.
Although pediatric thyroid cancer is rare, it has characteristics distinct from those of adult thyroid cancer. Thyroid nodules in children present a higher risk of malignancy, more frequent lymph node and distant metastases, and distinct molecular profiles compared to adults. Despite a more aggressive initial presentation, the long-term prognosis for children is excellent, with paradoxically low m...
BACKGROUND. Research on artificial intelligence (AI)-based computer-assisted detection and diagnosis (CADe/CADx) algorithms has focused primarily on digital mammography rather than on digital breast tomosynthesis (DBT). Additionally, DBT-related studies have not comprehensively stratified performance by cancer characteristics. OBJECTIVE. This study's purpose was to evaluate factors associated with...
PURPOSE: Exosome-surface enhanced Raman spectroscopy-artificial intelligence platform (exosome-SERS-AI) is an innovative liquid biopsy method that acq...
OBJECTIVES: Uniformity artifacts caused by defective transducer elements or scanner malfunctions degrade diagnostic image quality. Traditional quality...
Radiologic error remains an enduring challenge in diagnostic medicine. Despite study of radiologic error since the mid-twentieth century, interpretive...
In the rational design of novel polymers, the role of simulation methods based on classical physics is often hindered by the limited accuracy and tran...
Ultrasound can penetrate centimetres of soft tissue, focus energy with millimetre precision, and operate safely under real-time image guidance. Levera...
Giant cell arteritis (GCA) is a systemic vasculitis that predominantly affects mediumand large-sized arteries. Delayed diagnosis may result in irrever...
BACKGROUND AND OBJECTIVE: High resolution computed tomography (HRCT) scan diagnostic classification for usual interstitial pneumonia (UIP) plays a cri...
PURPOSE OF REVIEW: This review summarizes recent key advancements in multiple sclerosis (MS) achieved through the utilization of big data from diverse...
OBJECTIVE: Quantitative susceptibility mapping (QSM) is a useful magnetic resonance imaging technique. We aim to propose a deep learning (DL)-based me...
Diagnostic ultrasound has long filled a crucial niche in medical imaging thanks to its portability, affordability, and favorable safety profile. Now, ...
OBJECTIVE: Diffusion magnetic resonance imaging (dMRI) often suffers from low spatial and angular resolution due to inherent limitations in imaging ha...
OBJECTIVE: To achieve accurate 3-D reconstruction and quantitative analysis of human retinal vasculature from a single optical coherence tomography an...
The study of the nicotine addiction mechanism is of great significance in both nicotine withdrawal and brain science. The detection of addiction-relat...
Post-contrast 3D T1-weighted MRI is a time consuming component of cancer neuroimaing protocols. The goal of this study is to accelerate the acquisitio...
Accurate glioma genotype prediction, such as the isocitrate dehydrogenase (IDH) mutation and O6-methylguanine-DNA methyltransferase (MGMT) promoter me...
Purpose To develop and evaluate a Deep learnIng-bAsed MONoenergetic imaging at Different energies (DIAMOND) framework for generating virtual monoenerg...
As in many other fields, artificial intelligence (AI) is transforming daily activities in cardiology. In pharmacological therapy, algorithms have been...
BACKGROUND: Pulmonary ventilation imaging enables functional avoidance radiotherapy treatment plans by quantifying regional lung function. However, cu...