Radiology

Multiparametric MRI-based radiomics model for predicting human papillomavirus status in oropharyngeal squamous cell carcinoma: optimization using oversampling and machine learning techniques.

OBJECTIVES: To develop and validate a multiparametric MRI-based radiomics model with optimal oversam...

Reduced versus standard dose contrast volume for contrast-enhanced abdominal CT in overweight and obese patients using photon counting detector technology vs. second-generation dual-source energy integrating detector CT.

PURPOSE: To compare image quality of contrast-enhanced abdominal-CT using 1st-generation Dual Source...

Radiology under siege? Adversarial attacks against deep learning algorithms.

Evaluation of a Deep Learning Reconstruction for High-Quality T2-Weighted Breast Magnetic Resonance Imaging.

Deep learning (DL) reconstruction techniques to improve MR image quality are becoming commercially a...

Pressure support ventilation in intensive care patients receiving prolonged invasive ventilation.

To our knowledge, the use and management of pressure support ventilation (PSV) in patients receivin...

Deep Learning-Based Interpretable AI for Prostate T2W MRI Quality Evaluation.

RATIONALE AND OBJECTIVES: Prostate MRI quality is essential in guiding prostate biopsies. However, a...

Deep-learning segmentation method for optical coherence tomography angiography in ophthalmology.

PURPOSE: The optic disc and the macular are two major anatomical structures in the human eye. Optic ...

Deep learning based diagnosis of Alzheimer's disease using FDG-PET images.

PURPOSE: The aim of this study is to develop a deep neural network to diagnosis Alzheimer's disease ...

A multi-stage neural network approach for coronary 3D reconstruction from uncalibrated X-ray angiography images.

We present a multi-stage neural network approach for 3D reconstruction of coronary artery trees from...

Super-resolution biomedical imaging via reference-free statistical implicit neural representation.

Supervised deep learning for image super-resolution (SR) has limitations in biomedical imaging due t...

Update on ethical aspects in clinical research: Addressing concerns in the development of new AI tools in radiology.

The analysis of ethical aspects in clinical research has always been a challenge and has required co...

Impact of deep learning on radiologists and radiology residents in detecting breast cancer on CT: a cross-vendor test study.

AIM: To investigate the effect of deep learning on the diagnostic performance of radiologists and ra...

A multimodal deep learning model for predicting severe hemorrhage in placenta previa.

Placenta previa causes life-threatening bleeding and accurate prediction of severe hemorrhage leads ...

Exploring the performance of implicit neural representations for brain image registration.

Pairwise image registration is a necessary prerequisite for brain image comparison and data integrat...

The utility of automatic segmentation of kidney MRI in chronic kidney disease using a 3D convolutional neural network.

We developed a 3D convolutional neural network (CNN)-based automatic kidney segmentation method for ...

Knowledge and Perception of the Use of AI and its Implementation in the Field of Radiology: Cross-Sectional Study.

BACKGROUND: Artificial Intelligence (AI) has been developing for decades, but in recent years its us...

Development and validation of a CT-based deep learning algorithm to augment non-invasive diagnosis of idiopathic pulmonary fibrosis.

RATIONALE: Non-invasive diagnosis of idiopathic pulmonary fibrosis (IPF) involves identification of ...

AI as a New Frontier in Contrast Media Research: Bridging the Gap Between Contrast Media Reduction, the Contrast-Free Question and New Application Discoveries.

Artificial intelligence (AI) techniques are currently harnessed to revolutionize the domain of medic...

Unsupervised deep learning registration model for multimodal brain images.

Multimodal image registration is a key for many clinical image-guided interventions. However, it is ...

Democratizing Artificial Intelligence Imaging Analysis With Automated Machine Learning: Tutorial.

Deep learning-based clinical imaging analysis underlies diagnostic artificial intelligence (AI) mode...

U-Net based vessel segmentation for murine brains with small micro-magnetic resonance imaging reference datasets.

Identification and quantitative segmentation of individual blood vessels in mice visualized with pre...