Radiology

A comparison of point-tracking algorithms in ultrasound videos from the upper limb.

Tracking points in ultrasound (US) videos can be especially useful to characterize tissues in motion...

Deep Learning Detection and Segmentation of Brain Arteriovenous Malformation on Magnetic Resonance Angiography.

BACKGROUND: The delineation of brain arteriovenous malformations (bAVMs) is crucial for subsequent t...

Observer studies of image quality of denoising reduced-count cardiac single photon emission computed tomography myocardial perfusion imaging by three-dimensional Gaussian post-reconstruction filtering and deep learning.

BACKGROUND: The aim of this research was to asses perfusion-defect detection-accuracy by human obser...

AI-assisted compressed sensing and parallel imaging sequences for MRI of patients with nasopharyngeal carcinoma: comparison of their capabilities in terms of examination time and image quality.

OBJECTIVE: To compare examination time and image quality between artificial intelligence (AI)-assist...

Automatic brain MRI motion artifact detection based on end-to-end deep learning is similarly effective as traditional machine learning trained on image quality metrics.

Head motion artifacts in magnetic resonance imaging (MRI) are an important confounding factor concer...

Smart IoT in Breast Cancer Detection Using Optimal Deep Learning.

IoT in healthcare systems is currently a viable option for providing higher-quality medical care for...

Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis.

Background There is considerable interest in the potential use of artificial intelligence (AI) syste...

Deep Learning Aided Neuroimaging and Brain Regulation.

Currently, deep learning aided medical imaging is becoming the hot spot of AI frontier application a...

Prediction of Bone Marrow Biopsy Results From MRI in Multiple Myeloma Patients Using Deep Learning and Radiomics.

OBJECTIVES: In multiple myeloma and its precursor stages, plasma cell infiltration (PCI) and cytogen...

Academic integrity and artificial intelligence: is ChatGPT hype, hero or heresy?

Academic integrity in both higher education and scientific writing has been challenged by developmen...

Multimodality MRI synchronous construction based deep learning framework for MRI-guided radiotherapy synthetic CT generation.

Synthesizing computed tomography (CT) images from magnetic resonance imaging (MRI) data can provide ...

Deep learning-based classification of breast lesions using dynamic ultrasound video.

PURPOSE: We intended to develop a deep-learning-based classification model based on breast ultrasoun...

Uncertainty estimation for deep learning-based pectoral muscle segmentation via Monte Carlo dropout.

. Deep Learning models are often susceptible to failures after deployment. Knowing when your model i...

Inter-crystal scattering event identification using a novel silicon photomultiplier signal multiplexing method.

Identifying the inter-crystal scatter (ICS) events and recovering the first interaction position ena...

The Emerging Role of Automation, Measurement Standardization, and Artificial Intelligence in Foot and Ankle Imaging: An Update.

In the past few years, advances in clinical imaging in the realm of foot and ankle have been consequ...

Diagnosis of Liver Fibrosis Using Artificial Intelligence: A Systematic Review.

The development of liver fibrosis as a consequence of continuous inflammation represents a turning ...

Feasibility of accelerated non-contrast-enhanced whole-heart bSSFP coronary MR angiography by deep learning-constrained compressed sensing.

OBJECTIVES: To examine a compressed sensing artificial intelligence (CSAI) framework to accelerate i...

Deep learning for detection of iso-dense, obscure masses in mammographically dense breasts.

OBJECTIVES: To analyze the performance of deep learning in isodense/obscure masses in dense breasts....

Teaching Artificial Intelligence Literacy: A Challenge in the Education of Radiology Residents.

Deep learning regressor model based on nigrosome MRI in Parkinson syndrome effectively predicts striatal dopamine transporter-SPECT uptake.

PURPOSE: Nigrosome imaging using susceptibility-weighted imaging (SWI) and dopamine transporter imag...

Ultrafast Brain MRI Protocol at 1.5 T Using Deep Learning and Multi-shot EPI.

RATIONALE AND OBJECTIVES: To evaluate clinical feasibility and image quality of a comprehensive ultr...