Radiology

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

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Mitigating Aberration-Induced Noise: A Deep Learning-Based Aberration-to- Aberration Approach.

One of the primary sources of suboptimal image quality in ultrasound imaging is phase aberration. It...

Accurate Airway Tree Segmentation in CT Scans via Anatomy-Aware Multi-Class Segmentation and Topology-Guided Iterative Learning.

Intrathoracic airway segmentation in computed tomography is a prerequisite for various respiratory d...

PhraseAug: An Augmented Medical Report Generation Model With Phrasebook.

Medical report generation is a valuable and challenging task, which automatically generates accurate...

Medical Transformer: Universal Encoder for 3-D Brain MRI Analysis.

Transfer learning has attracted considerable attention in medical image analysis because of the limi...

Site-Invariant Meta-Modulation Learning for Multisite Autism Spectrum Disorders Diagnosis.

Large amounts of fMRI data are essential to building generalized predictive models for brain disease...

Deep learning-based body composition analysis from whole-body magnetic resonance imaging to predict all-cause mortality in a large western population.

BACKGROUND: Manually extracted imaging-based body composition measures from a single-slice area (A) ...

Three-Dimensional Thermal Tomography with Physics-Informed Neural Networks.

: Accurate reconstruction of internal temperature fields from surface temperature data is critical f...

A unique unsupervised enhanced intuitionistic fuzzy C-means for MR brain tissue segmentation.

The human-brain is a vital and complicated organ within the body. Identifying brain-related diseases...

Self-supervised graph contrastive learning with diffusion augmentation for functional MRI analysis and brain disorder detection.

Resting-state functional magnetic resonance imaging (rs-fMRI) provides a non-invasive imaging techni...

Evaluating AI proficiency in nuclear cardiology: Large language models take on the board preparation exam.

BACKGROUND: Previous studies evaluated the ability of large language models (LLMs) in medical discip...

Evaluation and comparison of synthetic computed tomography algorithms with 3T MRI for prostate radiotherapy: AI-based versus bulk density method.

PURPOSE: Synthetic computed tomography (sCT)-algorithms, which generate computed tomography images f...

AI-powered techniques in anatomical imaging: Impacts on veterinary diagnostics and surgery.

BACKGROUND: Artificial intelligence (AI) is rapidly transforming veterinary diagnostic imaging, offe...

Denoising low-field MR images with a deep learning algorithm based on simulated data from easily accessible open-source software.

In this study, we introduce a denoising method aimed at improving the contrast ratio in low-field MR...

Face mask identification with enhanced cuckoo optimization and deep learning-based faster regional neural network.

A mask identification and social distance monitoring system using Unmanned Aerial Vehicles (UAV) in ...

An explainable ultrasound-based machine learning model for predicting reproductive outcomes after frozen embryo transfer.

RESEARCH QUESTION: Can an optimal machine learning model be developed to predict reproductive outcom...

3D full-dose brain-PET volume recovery from low-dose data through deep learning: quantitative assessment and clinical evaluation.

OBJECTIVES: Low-dose (LD) PET imaging would lead to reduced image quality and diagnostic efficacy. W...

How reliable is artificial intelligence in the diagnosis of cholesteatoma on CT images?

PURPOSE: This study analysed the main artificial intelligence (AI) models for the diagnosis of chole...

The Role and Future of Artificial Intelligence in Robotic Image-Guided Interventions.

Artificial intelligence and robotics are transforming interventional radiology, driven by advancemen...

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