Radiology

Advancements in Imaging Sensors and AI for Plant Stress Detection: A Systematic Literature Review.

Integrating imaging sensors and artificial intelligence (AI) have contributed to detecting plant str...

Beyond the : Comparison of Artificial Intelligence Candidate and Radiologists on Mock Examinations for the Fellow of Royal College of Radiology Part B.

Predicting survival after radiosurgery in patients with lung cancer brain metastases using deep learning of radiomics and EGFR status.

The early prediction of overall survival (OS) in patients with lung cancer brain metastases (BMs) af...

Deep learning based MRI reconstruction with transformer.

Magnetic resonance imaging (MRI) has become one of the most powerful imaging techniques in medical d...

Deep Learning-Based Feature Extraction with MRI Data in Neuroimaging Genetics for Alzheimer's Disease.

The prognosis and treatment of patients suffering from Alzheimer's disease (AD) have been among the ...

Use of a Deep-Learning Algorithm to Guide Novices in Performing Focused Assessment With Sonography in Trauma.

An Automatic Breast Tumor Detection and Classification including Automatic Tumor Volume Estimation Using Deep Learning Technique.

OBJECTIVE: This study aims to develop automatic breast tumor detection and classification including ...

Optofluidic imaging meets deep learning: from merging to emerging.

Propelled by the striking advances in optical microscopy and deep learning (DL), the role of imaging...

Revolutionizing radiology with GPT-based models: Current applications, future possibilities and limitations of ChatGPT.

Artificial intelligence has demonstrated utility and is increasingly being used in the field of radi...

BUS-Set: A benchmark for quantitative evaluation of breast ultrasound segmentation networks with public datasets.

PURPOSE: BUS-Set is a reproducible benchmark for breast ultrasound (BUS) lesion segmentation, compri...

A Novel Convolutional Neural Network Model Based on Beetle Antennae Search Optimization Algorithm for Computerized Tomography Diagnosis.

Convolutional neural networks (CNNs) are widely used in the field of medical imaging diagnosis but h...

Deep Learning-Based Acceleration of Compressed Sensing for Noncontrast-Enhanced Coronary Magnetic Resonance Angiography in Patients With Suspected Coronary Artery Disease.

BACKGROUND: The clinical application of coronary MR angiography (MRA) remains limited due to its lon...

Deep-Learning-Based Whole-Lung and Lung-Lesion Quantification Despite Inconsistent Ground Truth: Application to Computerized Tomography in SARS-CoV-2 Nonhuman Primate Models.

RATIONALE AND OBJECTIVES: Animal modeling of infectious diseases such as coronavirus disease 2019 (C...

DEEP MOVEMENT: Deep learning of movie files for management of endovascular thrombectomy.

OBJECTIVES: Treatment and outcomes of acute stroke have been revolutionised by mechanical thrombecto...

A U-Shaped Network Based on Multi-level Feature and Dual-Attention Coordination Mechanism for Coronary Artery Segmentation of CCTA Images.

PURPOSE: Computed tomography coronary angiography (CCTA) images provide optimal visualization of cor...

Deep learning image reconstruction algorithm: impact on image quality in coronary computed tomography angiography.

PURPOSE: To perform a comprehensive intraindividual objective and subjective image quality evaluatio...

COVID-Net USPro: An Explainable Few-Shot Deep Prototypical Network for COVID-19 Screening Using Point-of-Care Ultrasound.

As the Coronavirus Disease 2019 (COVID-19) continues to impact many aspects of life and the global h...

Deep learning augmented ECG analysis to identify biomarker-defined myocardial injury.

Chest pain is a common clinical complaint for which myocardial injury is the primary concern and is ...

Molecular and functional imaging in cancer-targeted therapy: current applications and future directions.

Targeted anticancer drugs block cancer cell growth by interfering with specific signaling pathways v...

Letter From the Editor: Artificial Intelligence and Radiology.

Multi-path decoder U-Net: A weakly trained real-time segmentation network for object detection and localization in ultrasound scans.

Detecting and localizing an anatomical structure of interest within the field of view of an ultrasou...