Radiology

Accuracy of robot-assisted stereotactic MRI-guided laser ablation in children with epilepsy.

OBJECTIVE: Robot-assisted (RA) stereotactic MRI-guided laser ablation has been reported to be a safe and effective technique for the treatment of epileptogenic foci in children and adults. In this study the authors aimed to assess the accuracy of RA stereotactic MRI-guided laser fiber placement in children and to identify factors that might increase the risk of misplacement.

Radiomics and artificial intelligence for precision medicine in lung cancer treatment.

Lung cancer is the leading cause of cancer-related deaths worldwide. It exhibits, at the mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human eye but can be captured non-invasively on medical imaging as radiomic features, which can form a high dimensional data space amenable to machine learning. Radiomic features can be harnessed and used in an artificial inte...

Estimating Uncertainty in Neural Networks for Cardiac MRI Segmentation: A Benchmark Study.

OBJECTIVE: Convolutional neural networks (CNNs) have demonstrated promise in automated cardiac magnetic resonance image segmentation. However, when us...

Deep learning application for the classification of Alzheimer's disease using F-flortaucipir (AV-1451) tau positron emission tomography.

The positron emission tomography (PET) with F-flortaucipir can distinguish individuals with mild cognitive impairment (MCI) and Alzheimer's disease (A...

DGA3-Net: A parameter-efficient deep learning model for ASPECTS assessment for acute ischemic stroke using non-contrast computed tomography.

Detecting the early signs of stroke using non-contrast computerized tomography (NCCT) is essential for the diagnosis of acute ischemic stroke (AIS). H...

Physiological iodine uptake of the spine's bone marrow in dual-energy computed tomography - using artificial intelligence to define reference values based on 678 CT examinations of 189 individuals.

PURPOSE: The bone marrow's iodine uptake in dual-energy CT (DECT) is elevated in malignant disease. We aimed to investigate the physiological range of...

Precise angle estimation of capsule robot in ultrasound using heatmap guided two-stage network.

PURPOSE: A capsule robot can be controlled inside gastrointestinal (GI) tract by an external permanent magnet outside of human body for finishing non-...

Automatic Identification of Ultrasound Images of the Tibial Nerve in Different Ankle Positions Using Deep Learning.

Peripheral nerve tension is known to be related to the pathophysiology of neuropathy; however, assessing this tension is difficult in a clinical setti...

Automated 3-dimensional MRI segmentation for the posterosuperior rotator cuff tear lesion using deep learning algorithm.

INTRODUCTION: Rotator cuff tear (RCT) is a challenging and common musculoskeletal disease. Magnetic resonance imaging (MRI) is a commonly used diagnos...

Effect of artificial intelligence-based computer-aided diagnosis on the screening outcomes of digital mammography: a matched cohort study.

OBJECTIVE: To investigate whether artificial intelligence-based computer-aided diagnosis (AI-CAD) can improve radiologists' performance when used to s...

US regulatory considerations for low field magnetic resonance imaging systems.

Although there has been a resurgence of interest in low field magnetic resonance imaging (MRI) systems in recent years, low field MRI is not a new con...

Performance of ChatGPT on a Radiology Board-style Examination: Insights into Current Strengths and Limitations.

Background ChatGPT is a powerful artificial intelligence large language model with great potential as a tool in medical practice and education, but it...

Self-Propelled Janus Nanocatalytic Robots Guided by Magnetic Resonance Imaging for Enhanced Tumor Penetration and Therapy.

Biomedical micro/nanorobots as active delivery systems with the features of self-propulsion and controllable navigation have made tremendous progress ...

Artificial intelligence-driven radiomics study in cancer: the role of feature engineering and modeling.

Modern medicine is reliant on various medical imaging technologies for non-invasively observing patients' anatomy. However, the interpretation of medi...

Coronary Computed Tomography Angiography with Deep Learning Image Reconstruction: A Preliminary Study to Evaluate Radiation Exposure Reduction.

Coronary computed tomography angiography (CCTA) is a medical imaging technique that produces detailed images of the coronary arteries. Our work focuse...

Deep learning PET/CT-based radiomics integrates clinical data: A feasibility study to distinguish between tuberculosis nodules and lung cancer.

BACKGROUND: Radiomic diagnosis models generally consider only a single dimension of information, leading to limitations in their diagnostic accuracy a...

A Deep Learning Pipeline Using Prior Knowledge for Automatic Evaluation of Placenta Accreta Spectrum Disorders With MRI.

BACKGROUND: The diagnosis of prenatal placenta accreta spectrum (PAS) with magnetic resonance imaging (MRI) is highly dependent on radiologists' exper...

Deep learning-based reconstruction and 3D hybrid profile order technique for MRCP at 3T: evaluation of image quality and acquisition time.

OBJECTIVES: To evaluate the image quality of the 3D hybrid profile order technique and deep-learning-based reconstruction (DLR) for 3D magnetic resona...

Emerging uses of artificial intelligence in breast and axillary ultrasound.

Breast ultrasound is a valuable adjunctive tool to mammography in detecting breast cancer, especially in women with dense breasts. Ultrasound also pla...

Revenue and Cost Analysis of a System Utilizing Natural Language Processing and a Nurse Coordinator for Radiology Follow-up Recommendations.

Radiology reports often contain recommendations for follow-up imaging, Provider adherence to these radiology recommendations can be incomplete, which ...