Radiology

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

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Machine learning models for enhanced diagnosis and risk assessment of prostate cancer with Ga-PSMA-617 PET/CT.

OBJECTIVE: Prostate cancer (PCa) is highly heterogeneous, making early detection of adverse patholog...

An overview of utilizing artificial intelligence in localized prostate cancer imaging.

INTRODUCTION: Prostate cancer (PCa) is a leading cause of cancer-related deaths among men, and accur...

Machine learning prediction model for functional prognosis of acute ischemic stroke based on MRI radiomics of white matter hyperintensities.

OBJECTIVE: The purpose of the current study is to explore the value of a nomogram that integrates cl...

Machine learning reveals distinct neuroanatomical signatures of cardiovascular and metabolic diseases in cognitively unimpaired individuals.

Comorbid cardiovascular and metabolic risk factors (CVM) differentially impact brain structure and i...

Artificial intelligence in cardiovascular magnetic resonance imaging.

Artificial intelligence is rapidly evolving and its possibilities are endless. Its primary applicati...

Volume-based complete automation for ultrasound fetal biometry: A pilot approach to assess feasibility, reliability, and perspectives.

BACKGROUND: Detection algorithms targeting anatomic landmarks in three-dimensional (3D) ultrasound (...

CACTUS: An open dataset and framework for automated Cardiac Assessment and Classification of Ultrasound images using deep transfer learning.

Cardiac ultrasound (US) scanning is one of the most commonly used techniques in cardiology to diagno...

Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review.

PURPOSE: The purpose of this scoping review is to analyze the application of artificial intelligence...

Robust resolution improvement of 3D UTE-MR angiogram of normal vasculatures using super-resolution convolutional neural network.

Contrast-enhanced UTE-MRA provides detailed angiographic information but at the cost of prolonged sc...

Stages prediction of Alzheimer's disease with shallow 2D and 3D CNNs from intelligently selected neuroimaging data.

Detection of Alzheimer's Disease (AD) is critical for successful diagnosis and treatment, involving ...

Artificial intelligence-based incisive canal visualization for preventing and detecting post-implant injury, using cone beam computed tomography.

The aim of this study was to clinically validate an artificial intelligence (AI)-based tool for auto...

Preoperative Assessment of Ki-67 Labeling Index in Pituitary Adenomas Using Delta-Radiomics Based on Dynamic Contrast-Enhanced MRI.

BACKGROUND: Ki-67 labeling index (Ki-67 LI) is a proliferation marker that is correlated with aggres...

Dynamic glucose enhanced imaging using direct water saturation.

PURPOSE: Dynamic glucose enhanced (DGE) MRI studies employ CEST or spin lock (CESL) to study glucose...

A scoping review on the integration of artificial intelligence in point-of-care ultrasound: Current clinical applications.

BACKGROUND: Artificial intelligence (AI) is used increasingly in point-of-care ultrasound (POCUS). H...

Combining artificial intelligence assisted image segmentation and ultrasound based radiomics for the prediction of carotid plaque stability.

PURPOSE: Utilizing artificial intelligence (AI) technology for the segmentation of plaques on ultras...

LI-RADS-based hepatocellular carcinoma risk mapping using contrast-enhanced MRI and self-configuring deep learning.

BACKGROUND: Hepatocellular carcinoma (HCC) is often diagnosed using gadoxetate disodium-enhanced mag...

Artificial intelligence for predicting interstitial fibrosis and tubular atrophy using diagnostic ultrasound imaging and biomarkers.

BACKGROUND: Chronic kidney disease (CKD) is a global health concern characterised by irreversible re...

Real time artificial intelligence assisted carotid artery stenting: a preliminary experience.

BACKGROUND: Neurointerventionalists must pay close attention to multiple devices on multiple screens...

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