Radiology

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

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Differentiation between Phyllodes Tumors and Fibroadenomas through Breast Ultrasound: Deep-Learning Model Outperforms Ultrasound Physicians.

The preoperative differentiation of breast phyllodes tumors (PTs) from fibroadenomas (FAs) plays a c...

Evaluation of motion artefact reduction depending on the artefacts' directions in head MRI using conditional generative adversarial networks.

Motion artefacts caused by the patient's body movements affect magnetic resonance imaging (MRI) accu...

A divide and conquer approach to maximise deep learning mammography classification accuracies.

Breast cancer claims 11,400 lives on average every year in the UK, making it one of the deadliest di...

Transformer versus traditional natural language processing: how much data is enough for automated radiology report classification?

OBJECTIVES: Current state-of-the-art natural language processing (NLP) techniques use transformer de...

Calibrating Data Mismatches in Deep Learning-Based Quantitative Ultrasound Using Setting Transfer Functions.

Deep learning (DL) can fail when there are data mismatches between training and testing data distrib...

Decomposition of musculoskeletal structures from radiographs using an improved CycleGAN framework.

This paper presents methods of decomposition of musculoskeletal structures from radiographs into mul...

Graphic Intelligent Diagnosis of Hypoxic-Ischemic Encephalopathy Using MRI-Based Deep Learning Model.

INTRODUCTION: Heterogeneous MRI manifestations restrict the efficiency and consistency of neuroradio...

Prenatal Diagnosis of Placenta Accreta Spectrum Disorders: Deep Learning Radiomics of Pelvic MRI.

BACKGROUND: Diagnostic performance of placenta accreta spectrum (PAS) by prenatal MRI is unsatisfact...

Deep-learning-assisted and GPU-accelerated vector Doppler imaging with aliasing-resistant velocity estimation.

Vector flow imaging is a diagnostic ultrasound modality that is suited for the visualization of comp...

Development of a deep-learning model for classification of LI-RADS major features by using subtraction images of MRI: a preliminary study.

PURPOSE: Liver Imaging Reporting and Data System (LI-RADS) is limited by interreader variability. Th...

Neural network combining with clinical ultrasonography: A new approach for classification of salivary gland tumors.

OBJECTIVE: Little information is available about deep learning methods used in ultrasound images of ...

Deep Learning-Based Quantitative Assessment of Melamine and Cyanuric Acid in Pet Food Using Fourier Transform Infrared Spectroscopy.

Melamine and its derivative, cyanuric acid, are occasionally added to pet meals because of their nit...

A comparison of point-tracking algorithms in ultrasound videos from the upper limb.

Tracking points in ultrasound (US) videos can be especially useful to characterize tissues in motion...

Deep Learning Detection and Segmentation of Brain Arteriovenous Malformation on Magnetic Resonance Angiography.

BACKGROUND: The delineation of brain arteriovenous malformations (bAVMs) is crucial for subsequent t...

Smart IoT in Breast Cancer Detection Using Optimal Deep Learning.

IoT in healthcare systems is currently a viable option for providing higher-quality medical care for...

Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis.

Background There is considerable interest in the potential use of artificial intelligence (AI) syste...

Deep Learning Aided Neuroimaging and Brain Regulation.

Currently, deep learning aided medical imaging is becoming the hot spot of AI frontier application a...

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