Radiology

Quantitative noninvasive measurement of cerebrospinal fluid flow in shunted hydrocephalus.

OBJECTIVE: Standard MRI protocols lack a quantitative sequence that can be used to evaluate shunt-tr...

MGMT promoter methylation status prediction using MRI scans? An extensive experimental evaluation of deep learning models.

The number of studies on deep learning for medical diagnosis is expanding, and these systems are oft...

Improving radiology workflow using ChatGPT and artificial intelligence.

Artificial Intelligence is a branch of computer science that aims to create intelligent machines cap...

Potential Applications and Impact of ChatGPT in Radiology.

Radiology has always gone hand-in-hand with technology and artificial intelligence (AI) is not new t...

CT-based deep learning model: a novel approach to the preoperative staging in patients with peritoneal metastasis.

Peritoneal metastasis (PM) is a frequent manifestation of advanced abdominal malignancies. Accuratel...

Effects of MRI scanner manufacturers in classification tasks with deep learning models.

Deep learning has become a leading subset of machine learning and has been successfully employed in ...

Probabilistic Modeling for Image Registration Using Radial Basis Functions: Application to Cardiac Motion Estimation.

Cardiovascular diseases (CVDs) are the leading cause of death, affecting the cardiac dynamics over t...

The use of artificial intelligence tools in cancer detection compared to the traditional diagnostic imaging methods: An overview of the systematic reviews.

BACKGROUND AND PURPOSE: In comparison to conventional medical imaging diagnostic modalities, the aim...

Artificial intelligence to analyze magnetic resonance imaging in rheumatology.

Rheumatic disorders present a global health challenge, marked by inflammation and damage to joints, ...

Advancements in Positron Emission Tomography Detectors: From Silicon Photomultiplier Technology to Artificial Intelligence Applications.

This review article focuses on PET detector technology, which is the most crucial factor in determin...

Editorial Comment: Artificial Intelligence for Detection of Endotracheal Tube Malposition-Augmented Rather Than Autonomous Radiology Interpretation.

Enhancing the performance of premature ventricular contraction detection in unseen datasets through deep learning with denoise and contrast attention module.

Premature ventricular contraction (PVC) is a common and harmless cardiac arrhythmia that can be asym...

Complexities of deep learning-based undersampled MR image reconstruction.

Artificial intelligence has opened a new path of innovation in magnetic resonance (MR) image reconst...

Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions.

With the advent of large language models (LLMs), the artificial intelligence revolution in medicine ...

Improved precise guidewire delivery of a cardiovascular interventional surgery robot based on admittance control.

PURPOSE: The development of cardiovascular interventional surgery robots can realize master-slave in...

Radiomics-based machine learning and deep learning to predict serosal involvement in gallbladder cancer.

OBJECTIVE: Our study aimed to determine whether radiomics models based on contrast-enhanced computed...

Bayesian Convolutional Neural Networks in Medical Imaging Classification: A Promising Solution for Deep Learning Limits in Data Scarcity Scenarios.

Deep neural networks (DNNs) have already impacted the field of medicine in data analysis, classifica...

Deep Learning Based Parameterization of Diffeomorphic Image Registration for Cardiac Image Segmentation.

Cardiac segmentation from magnetic resonance imaging (MRI) is one of the essential tasks in analyzin...

From data to insights: how natural language processing and structured reporting advance data-driven radiology.

Deep learning for fast denoising filtering in ultrasound localization microscopy.

Addition of a denoising filter step in ultrasound localization microscopy (ULM) has been shown to ef...

A Shortened Model for Logan Reference Plot Implemented via the Self-Supervised Neural Network for Parametric PET Imaging.

Dynamic PET imaging provides superior physiological information than conventional static PET imaging...