Radiology

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

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Measuring the severity of knee osteoarthritis with an aberration-free fast line scanning Raman imaging system.

Osteoarthritis (OA) is a major cause of disability worldwide, with symptoms like joint pain, limited...

Development of Hybrid radiomic Machine learning models for preoperative prediction of meningioma grade on multiparametric MRI.

PURPOSE: To develop and compare machine learning models for distinguishing low and high grade mening...

Development and validation of automated three-dimensional convolutional neural network model for acute appendicitis diagnosis.

Rapid, accurate preoperative imaging diagnostics of appendicitis are critical in surgical decisions ...

Multi-task interaction learning for accurate segmentation and classification of breast tumors in ultrasound images.

In breast diagnostic imaging, the morphological variability of breast tumors and the inherent ambigu...

Fitness for Purpose of Text-to-Image Generative Artificial Intelligence Image Creation in Medical Imaging.

The recent emergence of text-to-image generative artificial intelligence (AI) diffusion models such ...

Impact of [F]FDG PET/CT Radiomics and Artificial Intelligence in Clinical Decision Making in Lung Cancer: Its Current Role.

Lung cancer remains one of the most prevalent cancers globally and the leading cause of cancer-relat...

Sustainable gelatin extraction from poultry skin-head-feet blend: An ultrasound-assisted approach.

The study investigated gelatin extraction from chicken skin-head-feet (SHF) blend using conventional...

Assessments of lung nodules by an artificial intelligence chatbot using longitudinal CT images.

Large language models have shown efficacy across multiple medical tasks. However, their value in the...

AI-Generated Synthetic STIR of the Lumbar Spine from T1 and T2 MRI Sequences Trained with Open-Source Algorithms.

BACKGROUND AND PURPOSE: Lumbar spine MRIs can be time consuming, stressful for patients, and costly ...

Artificial Intelligence-Generated Editorials in Radiology: Can Expert Editors Detect Them?

BACKGROUND AND PURPOSE: Artificial intelligence is capable of generating complex texts that may be i...

Prediction of Lymph Node Metastasis in Lung Cancer Using Deep Learning of Endobronchial Ultrasound Images With Size on CT and PET-CT Findings.

BACKGROUND AND OBJECTIVE: Echo features of lymph nodes (LNs) influence target selection during endob...

Deep learning based image enhancement for dynamic non-Cartesian MRI: Application to "silent" fMRI.

Radial based non-Cartesian sequences may be used for silent functional MRI examinations particularly...

Development and validation of a deep learning algorithm for prediction of pediatric recurrent intussusception in ultrasound images and radiographs.

PURPOSES: To develop a predictive model for recurrent intussusception based on abdominal ultrasound ...

Integrating radiomics into predictive models for low nuclear grade DCIS using machine learning.

Predicting low nuclear grade DCIS before surgery can improve treatment choices and patient care, the...

MRI radiomics based on machine learning in high-grade gliomas as a promising tool for prediction of CD44 expression and overall survival.

We aimed to predict CD44 expression and assess its prognostic significance in patients with high-gra...

Performance of a point-of-care ultrasound platform for artificial intelligence-enabled assessment of pulmonary B-lines.

BACKGROUND: The incorporation of artificial intelligence (AI) into point-of-care ultrasound (POCUS) ...

Generative AI for synthetic data across multiple medical modalities: A systematic review of recent developments and challenges.

This paper presents a comprehensive systematic review of generative models (GANs, VAEs, DMs, and LLM...

Use of deep learning-based high-resolution magnetic resonance to identify intracranial and extracranial symptom-related plaques.

This study aims to develop a deep learning model using high-resolution vessel wall imaging (HR-VWI) ...

Artificial intelligence-driven 3D MRI of lumbosacral nerve root anomalies: accuracy, incidence, and clinical utility.

PURPOSE: Lumbosacral nerve root anomalies are relatively rare but can be a risk factor for intraoper...

AI-powered prostate cancer detection: a multi-centre, multi-scanner validation study.

OBJECTIVES: Multi-centre, multi-vendor validation of artificial intelligence (AI) software to detect...

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