AIMC Topic:
Magnetic Resonance Imaging
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Evaluation of late gadolinium enhancement cardiac MRI using deep learning reconstruction.
Acta radiologica (Stockholm, Sweden : 1987)
Sep 12, 2023
BACKGROUND: Deep learning (DL)-based methods have been used to improve the imaging quality of magnetic resonance imaging (MRI) by denoising.
Deep learning, data ramping, and uncertainty estimation for detecting artifacts in large, imbalanced databases of MRI images.
Medical image analysis
Sep 9, 2023
Magnetic resonance imaging (MRI) is increasingly being used to delineate morphological changes underlying neurological disorders. Successfully detecting these changes depends on the MRI data quality. Unfortunately, image artifacts frequently compromi...
Deep Learning to Optimize Magnetic Resonance Imaging Prediction of Motor Outcomes After Hypoxic-Ischemic Encephalopathy.
Pediatric neurology
Sep 7, 2023
BACKGROUND: Magnetic resonance imaging (MRI) is the gold standard for outcome prediction after hypoxic-ischemic encephalopathy (HIE). Published scoring systems contain duplicative or conflicting elements.
Coupling synthetic and real-world data for a deep learning-based segmentation process of 4D flow MRI.
Computer methods and programs in biomedicine
Sep 6, 2023
BACKGROUND AND OBJECTIVE: Phase contrast magnetic resonance imaging (4D flow MRI) is an imaging technique able to provide blood velocity in vivo and morphological information. This capability has been used to study mainly the hemodynamics of large ve...
Fast deep learning reconstruction techniques for preclinical magnetic resonance fingerprinting.
NMR in biomedicine
Sep 5, 2023
We propose a deep learning (DL) model and a hyperparameter optimization strategy to reconstruct T and T maps acquired with the magnetic resonance fingerprinting (MRF) methodology. We applied two different MRF sequence routines to acquire images of ex...
Deep learning-based reconstruction can improve canine thoracolumbar magnetic resonance image quality and reduce slice thickness.
Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
Sep 5, 2023
In veterinary practice, thin-sliced thoracolumbar MRI is useful in detecting small lesions, especially in small-breed dogs. However, it is challenging due to the partial volume averaging effect and increase in scan time. Currently, deep learning-base...
Intra-frame motion deterioration effects and deep-learning-based compensation in MR-guided radiotherapy.
Medical physics
Sep 4, 2023
BACKGROUND: Current commercially available hybrid magnetic resonance linear accelerators (MR-Linac) use 2D+t cine MR imaging to provide intra-fractional motion monitoring. However, given the limited temporal resolution of cine MR imaging, target intr...
Deep learning-based segmentation of whole-body fetal MRI and fetal weight estimation: assessing performance, repeatability, and reproducibility.
European radiology
Sep 2, 2023
OBJECTIVES: To develop a deep-learning method for whole-body fetal segmentation based on MRI; to assess the method's repeatability, reproducibility, and accuracy; to create an MRI-based normal fetal weight growth chart; and to assess the sensitivity ...
Deep learning-based detection and quantification of brain metastases on black-blood imaging can provide treatment suggestions: a clinical cohort study.
European radiology
Sep 2, 2023
OBJECTIVES: We aimed to evaluate whether deep learning-based detection and quantification of brain metastasis (BM) may suggest treatment options for patients with BMs.
Detecting schizophrenia with 3D structural brain MRI using deep learning.
Scientific reports
Sep 2, 2023
Schizophrenia is a chronic neuropsychiatric disorder that causes distinct structural alterations within the brain. We hypothesize that deep learning applied to a structural neuroimaging dataset could detect disease-related alteration and improve clas...
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