Radiology

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Deployment of Artificial Intelligence in Radiology: Strategies for Success.

Radiology, as a highly technical and information-rich medical specialty, is well suited for artifici...

Artificial Intelligence-Based Fully Automated Quantitative Coronary Angiography vs Optical Coherence Tomography-Guided PCI: The FLASH Trial.

BACKGROUND: Recently developed artificial intelligence-based coronary angiography (AI-QCA, fully aut...

A cross-attention-based deep learning approach for predicting functional stroke outcomes using 4D CTP imaging and clinical metadata.

Acute ischemic stroke (AIS) remains a global health challenge, leading to long-term functional disab...

Real-World Performance of Pneumothorax-Detecting Artificial Intelligence Algorithm and its Impact on Radiologist Reporting Times.

RATIONALE AND OBJECTIVES: Artificial intelligence (AI) algorithms in radiology capable of detecting ...

Tracer-Separator: A Deep Learning Model for Brain PET Dual-Tracer ( 18 F-FDG and Amyloid) Separation.

INTRODUCTION: Multiplexed PET imaging revolutionized clinical decision-making by simultaneously capt...

GeSeNet: A General Semantic-Guided Network With Couple Mask Ensemble for Medical Image Fusion.

At present, multimodal medical image fusion technology has become an essential means for researchers...

Hierarchical Graph Convolutional Network Built by Multiscale Atlases for Brain Disorder Diagnosis Using Functional Connectivity.

Functional connectivity network (FCN) data from functional magnetic resonance imaging (fMRI) is incr...

Portable ultrasound devices for obstetric care in resource-constrained environments: mapping the landscape.

BACKGROUND: The WHO's recommendations on antenatal care underscore the need for ultrasound assessmen...

SDS-Net: A Synchronized Dual-Stage Network for Predicting Patients Within 4.5-h Thrombolytic Treatment Window Using MRI.

Timely and precise identification of acute ischemic stroke (AIS) within 4.5 h is imperative for effe...

Clinical Pilot of a Deep Learning Elastic Registration Algorithm to Improve Misregistration Artifact and Image Quality on Routine Oncologic PET/CT.

RATIONALE AND OBJECTIVES: Misregistration artifacts between the PET and attenuation correction CT (C...

Impact of deep Learning-enhanced contrast on diagnostic accuracy in stroke CT angiography.

PURPOSE: To examine the impact of deep learning-augmented contrast enhancement on image quality and ...

Deep Learning With Optical Coherence Tomography for Melanoma Identification and Risk Prediction.

Malignant melanoma is the most severe skin cancer with a rising incidence rate. Several noninvasive ...

Prediction of hepatocellular carcinoma response to radiation segmentectomy using an MRI-based machine learning approach.

PURPOSE: To evaluate the value of pre-treatment MRI-based radiomics in patients with hepatocellular ...

Evaluation of a deep learning-based software to automatically detect and quantify breast arterial calcifications on digital mammogram.

PURPOSE: The purpose of this study was to evaluate an artificial intelligence (AI) software that aut...

Charting the growth through intelligence: A SWOC analysis on AI-assisted radiologic bone age estimation.

Bone age estimation (BAE) is based on skeletal maturity and degenerative process of the skeleton. Th...

Impact of non-contrast-enhanced imaging input sequences on the generation of virtual contrast-enhanced breast MRI scans using neural network.

OBJECTIVE: To investigate how different combinations of T1-weighted (T1w), T2-weighted (T2w), and di...

Fetal Face: Enhancing 3D Ultrasound Imaging by Postprocessing With AI Applications: Myth, Reality, or Legal Concerns?

The use of artificial intelligence (AI) platforms is revolutionizing the performance in managing met...

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