Radiology

Deep learning-based image reconstruction for the multi-arterial phase images: improvement of the image quality to assess the small hypervascular hepatic tumor on gadoxetic acid-enhanced liver MRI.

PURPOSE: To evaluated the impact of a deep learning (DL)-based image reconstruction on multi-arteria...

[Validation of Optimal Imaging Conditions for Coronary Computed Tomography Angiography Using High-definition Mode and Deep Learning Image Reconstruction Algorithm].

PURPOSE: To verify the optimal imaging conditions for coronary computed tomography angiography (CCTA...

Abnormal Brachial Plexus Differentiation from Routine Magnetic Resonance Imaging: An AI-based Approach.

Automatic abnormality identification of brachial plexus (BP) from normal magnetic resonance imaging ...

The features associated with mammography-occult MRI-detected newly diagnosed breast cancer analysed by comparing machine learning models with a logistic regression model.

PURPOSE: To compare machine learning (ML) models with logistic regression model in order to identify...

Is there a truly significant reduction in blood loss comparing robot-assisted versus fluoroscopy-assisted pedicle screw implantation in scoliosis surgery?

Deep learning using contrast-enhanced ultrasound images to predict the nuclear grade of clear cell renal cell carcinoma.

PURPOSE: To assess the effectiveness of a deep learning model using contrastenhanced ultrasound (CEU...

Malignancy diagnosis of liver lesion in contrast enhanced ultrasound using an end-to-end method based on deep learning.

BACKGROUND: Contrast-enhanced ultrasound (CEUS) is considered as an efficient tool for focal liver l...

Multiparametric MRI-Based Interpretable Radiomics Machine Learning Model Differentiates Medulloblastoma and Ependymoma in Children: A Two-Center Study.

RATIONALE AND OBJECTIVES: Medulloblastoma (MB) and Ependymoma (EM) in children, share similarities i...

Financial impact of incorporating deep learning reconstruction into magnetic resonance imaging routine.

PURPOSE: Artificial intelligence and deep learning solutions are increasingly utilized in healthcare...

Unpaired deep learning for pharmacokinetic parameter estimation from dynamic contrast-enhanced MRI without AIF measurements.

DCE-MRI provides information about vascular permeability and tissue perfusion through the acquisitio...

Exploring the Low-Dose Limit for Focal Hepatic Lesion Detection with a Deep Learning-Based CT Reconstruction Algorithm: A Simulation Study on Patient Images.

This study aims to investigate the maximum achievable dose reduction for applying a new deep learnin...

Interventional Radiology is Now at the Confluence of Expertise, Innovation, and Artificial Intelligence.

How does deep learning/machine learning perform in comparison to radiologists in distinguishing glioblastomas (or grade IV astrocytomas) from primary CNS lymphomas?: a meta-analysis and systematic review.

BACKGROUND: Several studies have been published comparing deep learning (DL)/machine learning (ML) t...

RAPHIA: A deep learning pipeline for the registration of MRI and whole-mount histopathology images of the prostate.

Image registration can map the ground truth extent of prostate cancer from histopathology images ont...

Investigation of deep learning model for predicting immune checkpoint inhibitor treatment efficacy on contrast-enhanced computed tomography images of hepatocellular carcinoma.

Although the use of immune checkpoint inhibitors (ICIs)-targeted agents for unresectable hepatocellu...

Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer's disease in patients with mild cognitive symptoms.

BACKGROUND: Predicting future Alzheimer's disease (AD)-related cognitive decline among individuals w...

[Ethics and artificial intelligence].

The introduction of artificial intelligence (AI) into radiology promises to enhance efficiency and i...

Breaking boundaries in radiology: redefining AI diagnostics via raw data ahead of reconstruction.

In the realm of utilizing artificial intelligence (AI) for medical image analysis, the paradigm of '...

DDFC: deep learning approach for deep feature extraction and classification of brain tumors using magnetic resonance imaging in E-healthcare system.

This research explores the use of gated recurrent units (GRUs) for automated brain tumor detection u...

Comparison of the S8 navigation system and the TINAVI orthopaedic robot in the treatment of upper cervical instability.

The objective is to compare the clinical efficacy and safety of the S8 navigation system and the Tin...

Deep Learning Powered Identification of Differentiated Early Mesoderm Cells from Pluripotent Stem Cells.

Pluripotent stem cells can be differentiated into all three germ-layers including ecto-, endo-, and ...