Radiology

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

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Prior-FOVNet: A Multimodal Deep Learning Framework for Megavoltage Computed Tomography Truncation Artifact Correction and Field-of-View Extension.

Megavoltage computed tomography (MVCT) plays a crucial role in patient positioning and dose reconstr...

Predicting lymph node metastasis in thyroid cancer: systematic review and meta-analysis on the CT/MRI-based radiomics and deep learning models.

BACKGROUND: Thyroid cancer, a common endocrine malignancy, has seen increasing incidence, making lym...

Artificial intelligence and MRI in sinonasal tumors discrimination: where do we stand?

BACKGROUND: Artificial intelligence (AI) demonstrates high potential when applied to radiomic analys...

Ensemble learning-based radiomics model for discriminating brain metastasis from glioblastoma.

OBJECTIVE: Differentiating between brain metastasis (BM) and glioblastoma (GBM) preoperatively is ch...

A feature fusion method based on radiomic features and revised deep features for improving tumor prediction in ultrasound images.

BACKGROUND: Radiomic features and deep features are both vitally helpful for the accurate prediction...

Longitudinal interpretability of deep learning based breast cancer risk prediction.

Deep-learning-based models have achieved state-of-the-art breast cancer risk (BCR) prediction perfor...

Automated assessment of endometrial receptivity for screening recurrent pregnancy loss risk using deep learning-enhanced ultrasound and clinical data.

BACKGROUND: Recurrent pregnancy loss (RPL) poses significant challenges in clinical management due t...

A pilot evaluation of the diagnostic accuracy of ChatGPT-3.5 for multiple sclerosis from case reports.

The limitation of artificial intelligence (AI) large language models to diagnose diseases from the p...

The role of artificial intelligence in the diagnosis, imaging, and treatment of thoracic empyema.

PURPOSE OF REVIEW: The management of thoracic empyema is often complicated by diagnostic delays, rec...

Deep denoising approach to improve shear wave phase velocity map reconstruction in ultrasound elastography.

BACKGROUND: Measurement noise often leads to inaccurate shear wave phase velocity estimation in ultr...

CARS 2025 Computer Assisted Radiology and Surgery - 40th Anniversary and reflections on the role of modelling and AI.

PURPOSE: Based on CARS Congress events selected from its 40 year history, this editorial summarises ...

Automated Measurement of Effective Radiation Dose by F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography.

BACKGROUND/OBJECTIVES: Calculating the radiation dose from CT in F-PET/CT examinations poses a signi...

Machine Learning for Predicting Zearalenone Contamination Levels in Pet Food.

Zearalenone (ZEN) has been detected in both pet food ingredients and final products, causing acute t...

Multi-branch CNNFormer: a novel framework for predicting prostate cancer response to hormonal therapy.

PURPOSE: This study aims to accurately predict the effects of hormonal therapy on prostate cancer (P...

Comparison and analysis of deep learning models for discriminating longitudinal and oblique vaginal septa based on ultrasound imaging.

BACKGROUND: The longitudinal vaginal septum and oblique vaginal septum are female müllerian duct ano...

Machine Learning Driven by Magnetic Resonance Imaging for the Classification of Alzheimer Disease Progression: Systematic Review and Meta-Analysis.

BACKGROUND: To diagnose Alzheimer disease (AD), individuals are classified according to the severity...

AI in Dental Radiology-Improving the Efficiency of Reporting With ChatGPT: Comparative Study.

BACKGROUND: Structured and standardized documentation is critical for accurately recording diagnosti...

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