Radiology

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

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Denoising Diffusion Probabilistic Model to Simulate Contrast-enhanced spinal MRI of Spinal Tumors: A Multi-Center Study.

RATIONALE AND OBJECTIVES: To generate virtual T1 contrast-enhanced (T1CE) sequences from plain spina...

Deep Learning-Assisted Diagnosis of Malignant Cerebral Edema Following Endovascular Thrombectomy.

BACKGROUND: Malignant cerebral edema (MCE) is a significant complication following endovascular thro...

Complex-Valued Convolutional Gated Recurrent Neural Network for Ultrasound Beamforming.

Ultrasound detection is a potent tool for the clinical diagnosis of various diseases due to its real...

Enhanced U-Net for Infant Brain MRI Segmentation: A (2+1)D Convolutional Approach.

BACKGROUND: Infant brain tissue segmentation from MRI data is a critical task in medical imaging, pa...

GBCHV an advanced deep learning anatomy aware model for accurate classification of gallbladder cancer utilizing ultrasound images.

This study introduces a novel deep learning approach aimed at accurately classifying Gallbladder Can...

Repeatability-encouraging self-supervised learning reconstruction for quantitative MRI.

PURPOSE: The clinical value of quantitative MRI hinges on its measurement repeatability. Deep learni...

Deep Ensemble for Central Serous Microscopic Retinopathy Detection in Retinal Optical Coherence Tomographic Images.

The retina is an important part of the eye that aids in focusing light and visual recognition to the...

AutoDPS: An unsupervised diffusion model based method for multiple degradation removal in MRI.

BACKGROUND AND OBJECTIVE: Diffusion models have demonstrated their ability in image generation and s...

Living Microalgae-Based Magnetic Microrobots for Calcium Overload and Photodynamic Synergetic Cancer Therapy.

The combination of Ca overload and reactive oxygen species (ROS) production for cancer therapy offer...

Effectiveness of AI for Enhancing Computed Tomography Image Quality and Radiation Protection in Radiology: Systematic Review and Meta-Analysis.

BACKGROUND: Artificial intelligence (AI) presents a promising approach to balancing high image quali...

Predicting the efficacy of neoadjuvant chemotherapy in breast cancer patients based on ultrasound longitudinal temporal depth network fusion model.

OBJECTIVE: The aim of this study was to develop and validate a deep learning radiomics (DLR) model b...

T1-weighted MRI-based brain tumor classification using hybrid deep learning models.

Health is fundamental to human well-being, with brain health particularly critical for cognitive fun...

Machine learning-driven ultrasound radiomics for assessing axillary lymph node burden in breast cancer.

OBJECTIVE: This study explores the value of combining intratumoral and peritumoral radiomics feature...

Data-efficient generalization of AI transformers for noise reduction in ultra-fast lung PET scans.

PURPOSE: Respiratory motion during PET acquisition may produce lesion blurring. Ultra-fast 20-second...

Evaluation of MRI anatomy in machine learning predictive models to assess hydrogel spacer benefit for prostate cancer patients.

INTRODUCTION: Hydrogel spacers (HS) are designed to minimise the radiation doses to the rectum in pr...

Evaluation of AI-based nerve segmentation on ultrasound: relevance of standard metrics in the clinical setting.

BACKGROUND: In artificial intelligence for ultrasound-guided regional anaesthesia, accurate nerve id...

Post-Mortem imaging biobanks: Building data for reproducibility, standardization, and AI integration.

In recent years, post-mortem imaging has advanced with techniques such as Post-Mortem Computed Tomog...

The need for balancing 'black box' systems and explainable artificial intelligence: A necessary implementation in radiology.

Radiology is one of the medical specialties most significantly impacted by Artificial Intelligence (...

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