Radiology

Deep learning-based automatic pipeline for 3D needle localization on intra-procedural 3D MRI.

PURPOSE: Accurate and rapid needle localization on 3D magnetic resonance imaging (MRI) is critical f...

Comparison of model-based versus deep learning-based image reconstruction for thin-slice T2-weighted spin-echo prostate MRI.

PURPOSE: To compare a previous model-based image reconstruction (MBIR) with a newly developed deep l...

The Role of Prompt Engineering in Radiology Applications of Generative AI.

Deep Learning Accelerated Brain Diffusion-Weighted MRI with Super Resolution Processing.

OBJECTIVES: To investigate the clinical feasibility and image quality of accelerated brain diffusion...

Artificial Intelligence in Nuclear Cardiology: An Update and Future Trends.

Myocardial perfusion imaging (MPI), using either single photon emission computed tomography (SPECT) ...

Constantly optimized mean teacher for semi-supervised 3D MRI image segmentation.

The mean teacher model and its variants, as important methods in semi-supervised learning, have demo...

Automatic multi-view pose estimation in focused cardiac ultrasound.

Focused cardiac ultrasound (FoCUS) is a valuable point-of-care method for evaluating cardiovascular ...

A motion-corrected deep-learning reconstruction framework for accelerating whole-heart magnetic resonance imaging in patients with congenital heart disease.

BACKGROUND: Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessm...

Semi-supervised learning towards automated segmentation of PET images with limited annotations: application to lymphoma patients.

Manual segmentation poses a time-consuming challenge for disease quantification, therapy evaluation,...

Artificial Intelligence for Breast Cancer Risk Assessment.

Breast cancer risk prediction models based on common clinical risk factors are used to identify wome...

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...

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...

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...

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

Can we predict pathology without surgery? Weighing the added value of multiparametric MRI and whole prostate radiomics in integrative machine learning models.

OBJECTIVE: To test the ability of high-performance machine learning (ML) models employing clinical, ...

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...