Radiology

Performance of AI chatbots on controversial topics in oral medicine, pathology, and radiology.

OBJECTIVES: In this study, we assessed 6 different artificial intelligence (AI) chatbots (Bing, GPT-...

Quasi-supervised learning for super-resolution PET.

Low resolution of positron emission tomography (PET) limits its diagnostic performance. Deep learnin...

Deep learning-based PET image denoising and reconstruction: a review.

This review focuses on positron emission tomography (PET) imaging algorithms and traces the evolutio...

Artifact suppression for breast specimen imaging in micro CBCT using deep learning.

BACKGROUND: Cone-beam computed tomography (CBCT) has been introduced for breast-specimen imaging to ...

Image annotation and curation in radiology: an overview for machine learning practitioners.

"Garbage in, garbage out" summarises well the importance of high-quality data in machine learning an...

From jargon to clarity: Improving the readability of foot and ankle radiology reports with an artificial intelligence large language model.

BACKGROUND: The purpose of this study was to evaluate the efficacy of an Artificial Intelligence Lar...

Multicentric clinical evaluation of a computed tomography-based fully automated deep neural network for aortic maximum diameter and volumetric measurements.

OBJECTIVE: This study aims to evaluate a fully automatic deep learning-based method (augmented radio...

New perspectives on the use of artificial intelligence in the ultrasound evaluation of lung diseases.

Quantitative evaluation of Saliency-Based Explainable artificial intelligence (XAI) methods in Deep Learning-Based mammogram analysis.

BACKGROUND: Explainable Artificial Intelligence (XAI) is prominent in the diagnostics of opaque deep...

NPB-REC: A non-parametric Bayesian deep-learning approach for undersampled MRI reconstruction with uncertainty estimation.

The ability to reconstruct high-quality images from undersampled MRI data is vital in improving MRI ...

Artificial Intelligence Assistive Software Tool for Automated Detection and Quantification of Amyloid-Related Imaging Abnormalities.

IMPORTANCE: Amyloid-related imaging abnormalities (ARIA) are brain magnetic resonance imaging (MRI) ...

High-precision retinal blood vessel segmentation based on a multi-stage and dual-channel deep learning network.

The high-precision segmentation of retinal vessels in fundus images is important for the early diagn...

Magnetic resonance imaging-based radiomics and deep learning models for predicting lymph node metastasis of squamous cell carcinoma of the tongue.

OBJECTIVE: This study aimed to establish a combined method of radiomics and deep learning (DL) in ma...

Current Landscape of Advanced Imaging Tools for Pathology Diagnostics.

Histopathology relies on century-old workflows of formalin fixation, paraffin embedding, sectioning,...

Pedicle screw placement accuracy in robot-assisted versus image-guided freehand surgery of thoraco-lumbar spine (ROBARTHRODESE): study protocol for a single-centre randomized controlled trial.

BACKGROUND: Robotic spinal surgery may result in better pedicle screw placement accuracy, and reduct...

Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review.

Motion represents one of the major challenges in magnetic resonance imaging (MRI). Since the MR sign...

Phase Aberration Correction for In Vivo Ultrasound Localization Microscopy Using a Spatiotemporal Complex-Valued Neural Network.

Ultrasound Localization Microscopy (ULM) can map microvessels at a resolution of a few micrometers (...

deepPGSegNet: MRI-based pituitary gland segmentation using deep learning.

INTRODUCTION: In clinical research on pituitary disorders, pituitary gland (PG) segmentation plays a...

Applicable Machine Learning Model for Predicting Contrast-induced Nephropathy Based on Pre-catheterization Variables.

Automated abdominal adipose tissue segmentation and volume quantification on longitudinal MRI using 3D convolutional neural networks with multi-contrast inputs.

OBJECTIVE: Increased subcutaneous and visceral adipose tissue (SAT/VAT) volume is associated with ri...

Deep Learning Models Used in the Diagnostic Workup of Keratoconus: A Systematic Review and Exploratory Meta-Analysis.

PURPOSE: The prevalence of keratoconus in the general population is reported to be up to 1 of 84. Ov...