Radiology

Latest AI and machine learning research in radiology for healthcare professionals.

16,402 articles
Stay Ahead - Weekly Radiology research updates
Subscribe
Browse Categories
Showing 4747-4767 of 16,402 articles
How do patients perceive the AI-radiologists interaction? Results of a survey on 2119 responders.

PURPOSE: In this study we investigate how patients perceive the interaction between artificial intel...

Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging.

Machine-learning models for medical tasks can match or surpass the performance of clinical experts. ...

Using deep learning-derived image features in radiologic time series to make personalised predictions: proof of concept in colonic transit data.

OBJECTIVES: Siamese neural networks (SNN) were used to classify the presence of radiopaque beads as ...

Joint liver and hepatic lesion segmentation in MRI using a hybrid CNN with transformer layers.

UNLABELLED: Backgound and Objective: Deep learning-based segmentation of the liver and hepatic lesio...

A deep learning approach for radiological detection and classification of radicular cysts and periapical granulomas.

OBJECTIVES: Dentists and oral surgeons often face difficulties distinguishing between radicular cyst...

In situ sensing physiological properties of biological tissues using wireless miniature soft robots.

Implanted electronic sensors, compared with conventional medical imaging, allow monitoring of advanc...

Enhanced Deep Learning Model for Classification of Retinal Optical Coherence Tomography Images.

Retinal optical coherence tomography (OCT) imaging is a valuable tool for assessing the condition of...

Deep learning for predicting future lesion emergence in high-risk breast MRI screening: a feasibility study.

BACKGROUND: International societies have issued guidelines for high-risk breast cancer (BC) screenin...

A deep-learning model using enhanced chest CT images to predict PD-L1 expression in non-small-cell lung cancer patients.

AIM: To develop a deep-learning model using contrast-enhanced chest computed tomography (CT) images ...

Deep learning-based Lorentzian fitting of water saturation shift referencing spectra in MRI.

PURPOSE: Water saturation shift referencing (WASSR) Z-spectra are used commonly for field referencin...

Deep Learning Approaches with Digital Mammography for Evaluating Breast Cancer Risk, a Narrative Review.

Breast cancer remains the leading cause of cancer-related deaths in women worldwide. Current screeni...

Deep learning for automated detection of neovascular leakage on ultra-widefield fluorescein angiography in diabetic retinopathy.

Diabetic retinopathy is a leading cause of blindness in working-age adults worldwide. Neovascular le...

Surgical Sealant with Integrated Shape-Morphing Dual Modality Ultrasound and Computed Tomography Sensors for Gastric Leak Detection.

Postoperative anastomotic leaks are the most feared complications after gastric surgery. For diagnos...

3D surface reconstruction of cellular cryo-soft X-ray microscopy tomograms using semisupervised deep learning.

Cryo-soft X-ray tomography (cryo-SXT) is a powerful method to investigate the ultrastructure of cell...

(MARGOT) Monocular Camera-Based Robot Grasping Strategy for Metallic Objects.

Robotic handling of objects is not always a trivial assignment, even in teleoperation where, in most...

Deep learning model for automatic image quality assessment in PET.

BACKGROUND: A variety of external factors might seriously degrade PET image quality and lead to inco...

Deep learning phase error correction for cerebrovascular 4D flow MRI.

Background phase errors in 4D Flow MRI may negatively impact blood flow quantification. In this stud...

A Two-Branch Neural Network for Short-Axis PET Image Quality Enhancement.

The axial field of view (FOV) is a key factor that affects the quality of PET images. Due to hardwar...

Browse Categories