AIMC Topic: Diffusion Magnetic Resonance Imaging
Clear Filters Showing 131 to 140 of 338 articles
Simultaneous superresolution reconstruction and distortion correction for single-shot EPI DWI using deep learning.
Magnetic resonance in medicine
Jan 27, 2023
PURPOSE: Single-shot (SS) EPI is widely used for clinical DWI. This study aims to develop an end-to-end deep learning-based method with a novel loss function in an improved network structure to simultaneously increase the resolution and correct disto...
dtiRIM: A generalisable deep learning method for diffusion tensor imaging.
NeuroImage
Jan 24, 2023
Diffusion weighted MRI is an indispensable tool for routine patient screening and diagnostics of pathology. Recently, several deep learning methods have been proposed to quantify diffusion parameters, but poor generalisation to new data prevents broa...
Diffusion MRI data analysis assisted by deep learning synthesized anatomical images (DeepAnat).
Medical image analysis
Jan 19, 2023
Diffusion MRI is a useful neuroimaging tool for non-invasive mapping of human brain microstructure and structural connections. The analysis of diffusion MRI data often requires brain segmentation, including volumetric segmentation and cerebral cortic...
Automated deep-learning system in the assessment of MRI-visible prostate cancer: comparison of advanced zoomed diffusion-weighted imaging and conventional technique.
Cancer imaging : the official publication of the International Cancer Imaging Society
Jan 17, 2023
BACKGROUND: Deep-learning-based computer-aided diagnosis (DL-CAD) systems using MRI for prostate cancer (PCa) detection have demonstrated good performance. Nevertheless, DL-CAD systems are vulnerable to high heterogeneities in DWI, which can interfer...
Synthetic-to-real domain adaptation with deep learning for fitting the intravoxel incoherent motion model of diffusion-weighted imaging.
Medical physics
Jan 14, 2023
BACKGROUND: Intravoxel incoherent motion (IVIM) is a type of diffusion-weighted imaging (DWI), and IVIM model parameters (water molecule diffusion rate D , pseudo-diffusion coefficient D , and tissue perfusion fraction F ) have been widely used in th...
Deep learning prediction of diffusion MRI data with microstructure-sensitive loss functions.
Medical image analysis
Jan 13, 2023
Deep learning prediction of diffusion MRI (DMRI) data relies on the utilization of effective loss functions. Existing losses typically measure the signal-wise differences between the predicted and target DMRI data without considering the quality of d...
Automated estimation of ischemic core volume on noncontrast-enhanced CT via machine learning.
Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
Dec 26, 2022
BACKGROUND: Accurate estimation of ischemic core on baseline imaging has treatment implications in patients with acute ischemic stroke (AIS). Machine learning (ML) algorithms have shown promising results in estimating ischemic core using routine nonc...
Predicting Hypoperfusion Lesion and Target Mismatch in Stroke from Diffusion-weighted MRI Using Deep Learning.
Radiology
Dec 6, 2022
Background Perfusion imaging is important to identify a target mismatch in stroke but requires contrast agents and postprocessing software. Purpose To use a deep learning model to predict the hypoperfusion lesion in stroke and identify patients with ...
Feasibility of deep learning k-space-to-image reconstruction for diffusion weighted imaging in patients with breast cancers: Focus on image quality and reduced scan time.
European journal of radiology
Nov 13, 2022
PURPOSE: This study aimed to evaluate the feasibility of accelerated DLR (deep learning reconstruction) single-shot echo planar imaging (ss-EPI) for diffusion-weighted image (DWI) in patients with breast cancers in comparison to conventional ss-EPI.
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