Radiology

Artificial intelligence-powered coronary artery disease diagnosis from SPECT myocardial perfusion imaging: a comprehensive deep learning study.

BACKGROUND: Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPE...

Automated Coronary Artery Segmentation with 3D PSPNET using Global Processing and Patch Based Methods on CCTA Images.

The prevalence of coronary artery disease (CAD) has become the major cause of death across the world...

TRUSWorthy: toward clinically applicable deep learning for confident detection of prostate cancer in micro-ultrasound.

PURPOSE: While deep learning methods have shown great promise in improving the effectiveness of pros...

T2-weighted imaging of rectal cancer using a 3D fast spin echo sequence with and without deep learning reconstruction: A reader study.

PURPOSE: To compare image quality and clinical utility of a T2-weighted (T2W) 3-dimensional (3D) fas...

A multi-task self-supervised approach for mass detection in automated breast ultrasound using double attention recurrent residual U-Net.

Breast cancer is the most common and lethal cancer among women worldwide. Early detection using medi...

Intuitive Human-Artificial Intelligence Theranostic Complementarity.

Deep learning artificial intelligence (AI) algorithms are poised to subsume diagnostic imaging speci...

Artificial intelligence versus neurologists: A comparative study on multiple sclerosis expertise.

INTRODUCTION: Multiple sclerosis (MS) is an autoimmune neurodegenerative disease affecting the centr...

Assessment of breast composition in MRI using artificial intelligence - A systematic review.

INTRODUCTION: Magnetic Resonance Imaging (MRI) performs a critical role in breast cancer diagnosis, ...

Development of a Machine-Learning Algorithm to Identify Cauda Equina Compression on Magnetic Resonance Imaging Scans.

OBJECTIVE: Cauda equina syndrome (CES) poses significant neurological risks if untreated. Diagnosis ...

Robust Myocardial Perfusion MRI Quantification With DeepFermi.

Stress perfusion cardiac magnetic resonance is an important technique for examining and assessing th...

Intracranial stenosis prediction using a small set of risk factors in the Tromsø Study.

Intracranial atherosclerotic stenosis (ICAS) refers to a narrowing of intracranial arteries due to p...

Reinforcement-based leveraging transfer learning for multiclass optical coherence tomography images classification.

The accurate diagnosis of retinal diseases, such as Diabetic Macular Edema (DME) and Age-related Mac...

Artificial intelligence algorithm for preoperative prediction of FIGO stage in ovarian cancer based on clinical features integrated 18F-FDG PET/CT metabolic and radiomics features.

PURPOSE: The International Federation of Gynecology and Obstetric (FIGO) stage is critical to guidin...

Applications of Artificial Intelligence in Acute Thoracic Imaging.

The applications of artificial intelligence (AI) in radiology are rapidly advancing with AI algorith...

Equity in Radiology Research Is Essential for Improving Diversity and Inclusivity in Clinical Data, Reducing Bias and Increasing Artificial Intelligence Accuracy.

The scientific evidence of commercial AI products for MRI acceleration: a systematic review.

OBJECTIVES: This study explores the methods employed by commercially available AI products to accele...

Robust and generalizable artificial intelligence for multi-organ segmentation in ultra-low-dose total-body PET imaging: a multi-center and cross-tracer study.

PURPOSE: Positron Emission Tomography (PET) is a powerful molecular imaging tool that visualizes rad...

Prediction of adverse pathology in prostate cancer using a multimodal deep learning approach based on [F]PSMA-1007 PET/CT and multiparametric MRI.

PURPOSE: Accurate prediction of adverse pathology (AP) in prostate cancer (PCa) patients is crucial ...

SegFormer3D: Improving the Robustness of Deep Learning Model-Based Image Segmentation in Ultrasound Volumes of the Pediatric Hip.

Developmental dysplasia of the hip (DDH) is a painful orthopedic malformation diagnosed at birth in ...

A novel generative model for brain tumor detection using magnetic resonance imaging.

Brain tumors are a disease that kills thousands of people worldwide each year. Early identification ...

Multimodal deep learning fusion of ultrafast-DCE MRI and clinical information for breast lesion classification.

BACKGROUND: Breast cancer is the most common cancer worldwide, and magnetic resonance imaging (MRI) ...