AIMC Topic: Magnetic Resonance Angiography
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Denoising of high-resolution 3D UTE-MR angiogram data using lightweight and efficient convolutional neural networks.
Magnetic resonance imaging
Sep 1, 2025
High-resolution magnetic resonance angiography (∼ 50 μm MRA) data plays a critical role in the accurate diagnosis of various vascular disorders. However, it is very challenging to acquire, and it is susceptible to artifacts and noise which limits its...
Radiomics-Based Machine Learning Classification for Glioma Grading Using Diffusion- and Perfusion-Weighted Magnetic Resonance Imaging.
Journal of computer assisted tomography
May 13, 2025
OBJECTIVE: The aim of this study was to evaluate various radiomics-based machine learning classification models using the apparent diffusion coefficient (ADC) and cerebral blood flow (CBF) maps for differentiating between low-grade gliomas (LGGs) and...
Determinants of ascending aortic morphology: cross-sectional deep learning-based analysis on 25 073 non-contrast-enhanced NAKO MRI studies.
European heart journal. Cardiovascular Imaging
Apr 30, 2025
AIMS: Understanding determinants of thoracic aortic morphology is crucial for precise diagnostics and therapeutic approaches. This study aimed to automatically characterize ascending aortic morphology based on 3D non-contrast-enhanced magnetic resona...
Denoising using deep-learning-based reconstruction for whole-heart coronary MRA with sub-millimeter isotropic resolution at 3 T: a volunteer study.
Diagnostic and interventional radiology (Ankara, Turkey)
Sep 1, 2022
PURPOSE The aim of this study was to assess the usefulness of denoising deep-learning-based reconstruction (dDLR) to improve image quality and vessel delineation in noncontrast 3-T wholeheart coronary magnetic resonance angiography (WHCMRA) with sub-...
A Deep Learning Model with High Standalone Performance for Diagnosis of Unruptured Intracranial Aneurysm.
Yonsei medical journal
Nov 1, 2021
PURPOSE: This study aimed to investigate whether a deep learning model for automated detection of unruptured intracranial aneurysms on time-of-flight (TOF) magnetic resonance angiography (MRA) can achieve a target diagnostic performance comparable to...
[Computed tomography or cardiovascular magnetic resonance imaging for diagnosis of chronic coronary syndrome?].
Der Radiologe
Dec 1, 2020
BACKGROUND: Noninvasive imaging modalities are of central importance in the diagnosis of chronic coronary syndrome (CCS) in the current guidelines of the European Society of Cardiology (ESC), while the role of primary invasive coronary angiography in...
Incidental cerebral aneurysms detected by a computer-assisted detection system based on artificial intelligence: A case series.
Medicine
Oct 23, 2020
RATIONALE: Computer-assisted detection (CAD) systems based on artificial intelligence (AI) using convolutional neural network (CNN) have been successfully used for the diagnosis of unruptured cerebral aneurysms in experimental situations. However, it...
Patient-specific three-dimensional aortic arch modeling for automatic measurements: clinical validation in aortic coarctation.
Journal of cardiovascular medicine (Hagerstown, Md.)
Jul 1, 2020
AIM: A validated algorithm for automatic aortic arch measurements in aortic coarctation (CoA) patients could standardize procedures for clinical planning.
Models, Cardiovascular
Retrospective Studies
Patient-Specific Modeling
Aortic Coarctation
Female
Automation
Reproducibility of Results
Aorta, Thoracic
Adolescent
Magnetic Resonance Angiography
Humans
Young Adult
Child
Imaging, Three-Dimensional
Machine Learning
Adult
Predictive Value of Tests
Software
Male
A data-driven update of arterial perfusion territories.
Nature reviews. Neurology
Nov 1, 2019
Convolutional Neural Networks for the Detection and Measurement of Cerebral Aneurysms on Magnetic Resonance Angiography.
Journal of digital imaging
Oct 1, 2019
Aneurysm size correlates with rupture risk and is important for treatment planning. User annotation of aneurysm size is slow and tedious, particularly for large data sets. Geometric shortcuts to compute size have been shown to be inaccurate, particul...
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