Radiology

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

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Inclusive AI for radiology: Optimising ChatGPT-4 with advanced prompt engineering.

This letter responds to the article "Encouragement vs. liability: How prompt engineering influences ...

Current status and future directions of explainable artificial intelligence in medical imaging.

The inherent "black box" nature of AI algorithms presents a substantial barrier to the widespread ad...

A multi-view learning approach with diffusion model to synthesize FDG PET from MRI T1WI for diagnosis of Alzheimer's disease.

INTRODUCTION: This study presents a novel multi-view learning approach for machine learning (ML)-bas...

Diagnostic modalities in the mediastinum and the role of bronchoscopy in mediastinal assessment: a narrative review.

BACKGROUND AND OBJECTIVE: Diagnosis of pathology in the mediastinum has proven quite challenging, gi...

Deep Learning for Contrast Enhanced Mammography - A Systematic Review.

BACKGROUND/AIM: Contrast-enhanced mammography (CEM) is a relatively novel imaging technique that ena...

Evaluating CNN Architectures for the Automated Detection and Grading of Modic Changes in MRI: A Comparative Study.

OBJECTIVE: Modic changes (MCs) classification system is the most widely used method in magnetic reso...

A multi-view prognostic model for diffuse large B-cell lymphoma based on kernel canonical correlation analysis and support vector machine.

BACKGROUND AND OBJECTIVE: Positron emission tomography/computed tomography (PET/CT) is recommended a...

Detection of three-rooted mandibular first molars on panoramic radiographs using deep learning.

This study aimed to develop a deep learning system for the detection of three-rooted mandibular firs...

Generative models of MRI-derived neuroimaging features and associated dataset of 18,000 samples.

Availability of large and diverse medical datasets is often challenged by privacy and data sharing r...

Accuracy of radiologists and radiology residents in detection of paediatric appendicular fractures with and without artificial intelligence.

OBJECTIVES: We aim to evaluate the accuracy of radiologists and radiology residents in the detection...

DPFNet: Fast Reconstruction of Multi-Coil MRI Based on Dual Domain Parallel Fusion Network.

There are relatively few studies on the multi-coil reconstruction task of existing Magnetic Resonanc...

Deep-DM: Deep-Driven Deformable Model for 3D Image Segmentation Using Limited Data.

Objective - Medical image segmentation is essential for several clinical tasks, including diagnosis,...

Generalized Super-Resolution 4D Flow MRI - Using Ensemble Learning to Extend Across the Cardiovascular System.

4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique capable of ...

tDKI-Net: A Joint q-t Space Learning Network for Diffusion-Time-Dependent Kurtosis Imaging.

Time-dependent diffusion magnetic resonance imaging (TDDMRI) is useful for the non-invasive characte...

Comparing effects of wearable robot-assisted gait training on functional changes and neuroplasticity: A preliminary study.

Robot-assisted gait training (RAGT) is a promising technique for improving the gait ability of elder...

Topology aware multitask cascaded U-Net for cerebrovascular segmentation.

Cerebrovascular segmentation is a crucial preliminary task for many computer-aided diagnosis tools d...

Large Language Models with Vision on Diagnostic Radiology Board Exam Style Questions.

RATIONALE AND OBJECTIVES: The expansion of large language models to process images offers new avenue...

Leveraging a Vision Transformer Model to Improve Diagnostic Accuracy of Cardiac Amyloidosis With Cardiac Magnetic Resonance.

BACKGROUND: Cardiac magnetic resonance (CMR) imaging is an important diagnostic tool for diagnosis o...

A multimodal machine learning model for the stratification of breast cancer risk.

Machine learning models for the diagnosis of breast cancer can facilitate the prediction of cancer r...

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