Radiology

Protective Effects of Riociguat Against Contrast-Induced Nephropathy: An Experimental and Machine Learning-Based Study in Rats.

Contrast-induced nephropathy (CIN) is an important cause of acute kidney injury following exposure to iodinated contrast media, and effective preventive strategies remain limited. This study investigated the renoprotective effects of riociguat, a soluble guanylate cyclase stimulator, in an experimental rat model of CIN and explored machine-learning-based prediction of renal injury using histopatho...

Machine Learning-Enhanced Raman Spectroscopy for Microfiber Detection: From Model Development to Coastal Investigation.

Microfibers are recognized as the most prevalent form of microplastics, with a widespread distribution across various ecosystems. The distinctive morphology of microfibers provides additional insights into their detection. In contrast to most studies targeting microplastic identification, this study proposed a rapid detection method for microfibers utilizing Raman spectroscopy and machine learning...

Artificial intelligence iterative reconstruction in lower extremity computed tomography angiography (CTA) of diabetic patients: Improved visualization of distal and collateral arteries.

BackgroundThe impact of deep learning (DL)-based computed tomography (CT) reconstruction on the visualization of distal and collateral arteries in dia...

Integration of detection and tracking networks for automated rib multiplanar reconstruction: a feasibility study for fracture diagnosis.

OBJECTIVE: Rib fractures are common yet time-consuming to diagnose. This study explores automation via multiplanar reconstruction and intelligent dete...

Diagnostic performance and confidence of an optimized deep-learning algorithm for the detection of intracranial hemorrhages.

OBJECTIVES: To evaluate the performance of an optimized deep-learning-based algorithm (AI) for the detection and subtyping of intracranial hemorrhage ...

Application value of gastric contrast ultrasonography in gastric tumors.

In recent years, gastric oral contrast ultrasonography (OCUS) and double contrast-enhanced ultrasonography (DCEUS) have emerged as promising imaging t...

Value of Endobronchial Ultrasound-Derived Radiomics in Differentiating Pulmonary Sarcoidosis from Mediastinal Lymph Node Tuberculosis.

INTRODUCTION: To explore the feasibility of an ultrasound radiomics machine learning model based on endobronchial ultrasound (EBUS) for differentiatin...

Rectal Cancer Radiotherapy Response Prediction: Retrospective Study of Development of a Deep Learning-Based Radiomics Model.

Background: Radiotherapy (RT) is a cornerstone of multimodal treatment for rectal cancer (RC); yet, substantial interindividual variability in treatme...

SSI-Net: A hybrid physics-constrained deep learning framework for quantitative ultrasound speed-of-sound reconstruction.

OBJECTIVE: Quantitative ultrasound tomography faces challenges in reconstructing speed‑of‑sound (SoS) distributions due to the ill‑posed nature of the...

NNTV-GS：A fast reconstruction method combining nearest neighbor total variation and Gaussian splatting in dental offset detector CBCT.

OBJECTIVE: This study aims to address the slow reconstruction speed of iterative reconstruction algorithms in dental cone-beam computed tomography (CB...

Flow-QSM: bridging learned priors and physical models for quantitative susceptibility mapping.

OBJECTIVE: Quantitative Susceptibility Mapping (QSM) is a magnetic resonance imaging technique that quantifies tissue magnetic susceptibility by s...

Minimally invasive spine surgery: current advantages, limitations, and future directions.

Minimally invasive spine surgery (MISS), supported by advancements in endoscopic systems, tubular retractors, lateral access corridors, image-guided n...

Comparison of Left Ventricular Ejection Fraction Among 18F-FDG Dual-Gated PET/CT, Single-Gated PET/MRI, and Cardiac MRI.

Left ventricular ejection fraction (LVEF) is a critical parameter in the evaluation of cardiac function, and its measurement can guide treatment decis...

Accuracy of Diagnosis and Anticipation of Future Treatment in Pediatric Peripelvic Infections: The Role of Multisurgeon Review and Implications for Future Machine Learning Algorithms.

INTRODUCTION: MRI is commonly used to evaluate pelvic musculoskeletal infections. Limited "quick" MRI protocols enable timely imaging without intraven...

Integrated molecular and clinical profiling of primary mitochondrial oxidative phosphorylation disorders in an Indian cohort: Insights from genetics, neuroimaging, and machine learning.

Primary mitochondrial disorders are clinically and genetically heterogeneous and remain underdiagnosed in resource-limited settings. We performed a re...

Ultrasonic-assisted extraction, purification, identification, and bioactivity evaluation of phlorotannins from Sargassum fusiforme: A comparative study of RSM and SVM-GA.

Sargassum fusiforme is a medicinal and edible species present in China, Korea, and Japan, and its phlorotannins are considered valuable bioactive comp...

Prediction of thermally driven quasi-1D superionic states in carbon hydride under giant planetary conditions.

Planetary interiors experience high-pressure-high temperature conditions that give rise to unconventional states of matter, reshaping our understandin...

Coronary artery disease diagnosis with signal processing and machine learning of heart sound signals: a systematic review.

Coronary artery disease (CAD) remains a major contributor to morbidity and mortality worldwide. Heart sound analysis has been investigated as a noninv...

Automated Prediction of Radiological Protocols Using Retrieval Augmented Generation.

Radiological protocol selection is a critical but time-consuming step in clinical workflow, requiring radiologists to match patient indications with a...

[Magnetic resonance imaging in dementia].

Magnetic resonance imaging (MRI) plays a pivotal role in the diagnostic work-up of dementia. In addition to excluding secondary and potentially treata...