Radiology

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

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In vivo evaluation of complex polyps with endoscopic optical coherence tomography and deep learning during routine colonoscopy: a feasibility study.

Standard-of-care (SoC) imaging for assessing colorectal polyps during colonoscopy, based on white-li...

Deep learning of structural MRI predicts fluid, crystallized, and general intelligence.

Can brain structure predict human intelligence? T1-weighted structural brain magnetic resonance imag...

Feasibility of Ultra-low Radiation and Contrast Medium Dosage in Aortic CTA Using Deep Learning Reconstruction at 60 kVp: An Image Quality Assessment.

OBJECTIVE: To assess the viability of using ultra-low radiation and contrast medium (CM) dosage in a...

Water-Stable Magnetic Lipiodol Micro-Droplets as a Miniaturized Robotic Tool for Drug Delivery.

Magnetic microrobots, designed to navigate the complex environments of the human body, show promise ...

From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients.

With the increasing demand for precision medicine in cancer patients, radiogenomics emerges as a pro...

Brain tumor diagnosis in MRI scans images using Residual/Shuffle Network optimized by augmented Falcon Finch optimization.

Brain tumor diagnosis is an important task in prognosing and treatment planning of the patients with...

Radiologic imaging biomarkers in triple-negative breast cancer: a literature review about the role of artificial intelligence and the way forward.

Breast cancer is one of the most common and deadly cancers in women. Triple-negative breast cancer (...

Machine learning algorithms using the inflammatory prognostic index for contrast-induced nephropathy in NSTEMI patients.

Inflammatory prognostic index (IPI), has been shown to be related with poor outcomes in cancer pati...

Development of a Deep Learning Model for Classification of Hepatic Steatosis from Clinical Standard Ultrasound.

OBJECTIVE: Early detection and monitoring of hepatic steatosis can help establish appropriate preven...

Segmentation of breast lesion using fuzzy thresholding and deep learning.

Breast cancer is a major cause of morbidity and mortality in women. In breast cancer screening, Dyna...

Visualizing radiological data bias through persistence images.

Persistence images, derived from topological data analysis, emerge as a powerful tool for visualizin...

Persistence landscapes: Charting a path to unbiased radiological interpretation.

Persistence landscapes, a sophisticated tool from topological data analysis, offer a promising appro...

A F-FDG PET/CT-based deep learning-radiomics-clinical model for prediction of cervical lymph node metastasis in esophageal squamous cell carcinoma.

BACKGROUND: To develop an artificial intelligence (AI)-based model using Radiomics, deep learning (D...

Brain imaging and machine learning reveal uncoupled functional network for contextual threat memory in long sepsis.

Positron emission tomography (PET) utilizes radiotracers like [F]fluorodeoxyglucose (FDG) to measure...

High-precision MRI of liver and hepatic lesions on gadoxetic acid-enhanced hepatobiliary phase using a deep learning technique.

PURPOSE: The purpose of this study was to investigate whether the high-precision magnetic resonance ...

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