Radiology

From Diagnosis to Precision Surgery: The Transformative Role of Artificial Intelligence in Urologic Imaging.

The multidisciplinary nature of artificial intelligence (AI) has allowed for rapid growth of its app...

Cross-attention enables deep learning on limited omics-imaging-clinical data of 130 lung cancer patients.

Deep-learning tools that extract prognostic factors derived from multi-omics data have recently cont...

GREnet: Gradually REcurrent Network With Curriculum Learning for 2-D Medical Image Segmentation.

Medical image segmentation is a vital stage in medical image analysis. Numerous deep-learning method...

Ultrasound-based nomogram to predict the recurrence in papillary thyroid carcinoma using machine learning.

BACKGROUND AND AIMS: The recurrence of papillary thyroid carcinoma (PTC) is not unusual and associat...

Machine Learning Based Prediction of Post-operative Infrarenal Endograft Apposition for Abdominal Aortic Aneurysms.

OBJECTIVE: Challenging infrarenal aortic neck characteristics have been associated with an increased...

Fast, high-quality, and unshielded 0.2 T low-field mobile MRI using minimal hardware resources.

OBJECTIVE: To propose a deep learning-based low-field mobile MRI strategy for fast, high-quality, un...

Artificial intelligence-based evaluation of carotid artery compressibility via point-of-care ultrasound in determining the return of spontaneous circulation during cardiopulmonary resuscitation.

AIM: This study introduces RealCAC-Net, an artificial intelligence (AI) system, to quantify carotid ...

AI driven analysis of MRI to measure health and disease progression in FSHD.

Facioscapulohumeral muscular dystrophy (FSHD) affects roughly 1 in 7500 individuals. While at the po...

Accelerated High-Resolution Deep Learning Reconstruction Turbo Spin Echo MRI of the Knee at 7 T.

OBJECTIVES: The aim of this study was to compare the image quality of 7 T turbo spin echo (TSE) knee...

Deep learning-based segmentation of left ventricular myocardium on dynamic contrast-enhanced MRI: a comprehensive evaluation across temporal frames.

PURPOSE: Cardiac perfusion MRI is vital for disease diagnosis, treatment planning, and risk stratifi...

Multicenter validation study for automated left ventricular ejection fraction assessment using a handheld ultrasound with artificial intelligence.

We sought to validate the ability of a novel handheld ultrasound device with an artificial intellige...

Neuroimaging and natural language processing-based classification of suicidal thoughts in major depressive disorder.

Suicide is a growing public health problem around the world. The most important risk factor for suic...

Single-Subject Deep-Learning Image Reconstruction With a Neural Optimization Transfer Algorithm for PET-Enabled Dual-Energy CT Imaging.

Combining dual-energy computed tomography (DECT) with positron emission tomography (PET) offers many...

Investing in Artificial Intelligence and Digital Health-What Radiology Innovators Need to Know.

Expected to grow at a 5.5% compound annual growth rate and reach a market of $34.6 billion by 2028, ...

Super-resolution deep learning reconstruction approach for enhanced visualization in lumbar spine MR bone imaging.

OBJECTIVES: This study aims to assess the effectiveness of super-resolution deep-learning-based reco...

Development and validation of a deep learning-based method for automatic measurement of uterus, fibroid, and ablated volume in MRI after MR-HIFU treatment of uterine fibroids.

INTRODUCTION: The non-perfused volume divided by total fibroid load (NPV/TFL) is a predictive outcom...

Characterizing Sentinel Lymph Node Status in Breast Cancer Patients Using a Deep-Learning Model Compared With Radiologists' Analysis of Grayscale Ultrasound and Lymphosonography.

The objective of the study was to use a deep learning model to differentiate between benign and mali...

Editorial Comment: Enhancing Radiologist Sensitivity for Incidental Pulmonary Embolism Detection With Artificial Intelligence-A Prospective Validation Study.

Deep learning-based image quality assessment: impact on detection accuracy of prostate cancer extraprostatic extension on MRI.

OBJECTIVE: To assess impact of image quality on prostate cancer extraprostatic extension (EPE) detec...

Structure focused neurodegeneration convolutional neural network for modelling and classification of Alzheimer's disease.

Alzheimer's disease (AD), the predominant form of dementia, is a growing global challenge, emphasizi...

Prostate cancer risk assessment and avoidance of prostate biopsies using fully automatic deep learning in prostate MRI: comparison to PI-RADS and integration with clinical data in nomograms.

OBJECTIVES: Risk calculators (RCs) improve patient selection for prostate biopsy with clinical/demog...