Research progress of machine learning and deep learning in intelligent diagnosis of the coronary atherosclerotic heart disease
H Lu, Y Yao, L Wang, J Yan, S Tu… - … Methods in Medicine, 2022 - Wiley Online Library
The coronary atherosclerotic heart disease is a common cardiovascular disease with high
morbidity, disability, and societal burden. Early, precise, and comprehensive diagnosis of …
morbidity, disability, and societal burden. Early, precise, and comprehensive diagnosis of …
Superconducting magnet designs and MRI accessibility: A review
M Manso Jimeno, JT Vaughan… - NMR in …, 2023 - Wiley Online Library
Presently, magnetic resonance imaging (MRI) magnets must deliver excellent magnetic field
(B0) uniformity to achieve optimum image quality. Long magnets can satisfy the …
(B0) uniformity to achieve optimum image quality. Long magnets can satisfy the …
Fully automated, quality-controlled cardiac analysis from CMR: validation and large-scale application to characterize cardiac function
Objectives This study sought to develop a fully automated framework for cardiac function
analysis from cardiac magnetic resonance (CMR), including comprehensive quality control …
analysis from cardiac magnetic resonance (CMR), including comprehensive quality control …
[HTML][HTML] Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning
Good quality of medical images is a prerequisite for the success of subsequent image
analysis pipelines. Quality assessment of medical images is therefore an essential activity …
analysis pipelines. Quality assessment of medical images is therefore an essential activity …
Deep learning‐based motion quantification from k‐space for fast model‐based magnetic resonance imaging motion correction
Background Intra‐scan rigid‐body motion is a costly and ubiquitous problem in clinical
magnetic resonance imaging (MRI) of the head. Purpose State‐of‐the‐art methods for …
magnetic resonance imaging (MRI) of the head. Purpose State‐of‐the‐art methods for …
Deep learning-based detection and correction of cardiac MR motion artefacts during reconstruction for high-quality segmentation
Segmenting anatomical structures in medical images has been successfully addressed with
deep learning methods for a range of applications. However, this success is heavily …
deep learning methods for a range of applications. However, this success is heavily …
Cine cardiac MRI motion artifact reduction using a recurrent neural network
Cine cardiac magnetic resonance imaging (MRI) is widely used for the diagnosis of cardiac
diseases thanks to its ability to present cardiovascular features in excellent contrast. As …
diseases thanks to its ability to present cardiovascular features in excellent contrast. As …
ArtifactID: Identifying artifacts in low-field MRI of the brain using deep learning
Low-field MR scanners are more accessible in resource-constrained settings where skilled
personnel are scarce. Images acquired in such scenarios are prone to artifacts such as wrap …
personnel are scarce. Images acquired in such scenarios are prone to artifacts such as wrap …
Motion artifacts reduction in brain MRI by means of a deep residual network with densely connected multi-resolution blocks (DRN-DCMB)
J Liu, M Kocak, M Supanich, J Deng - Magnetic resonance imaging, 2020 - Elsevier
Objective: Magnetic resonance imaging (MRI) acquisition is inherently sensitive to motion,
and motion artifact reduction is essential for improving image quality in MRI. Methods: We …
and motion artifact reduction is essential for improving image quality in MRI. Methods: We …
Brain MRI artefact detection and correction using convolutional neural networks
I Oksuz - Computer methods and programs in biomedicine, 2021 - Elsevier
Abstract Background and Objective: Brain MRI is one of the most commonly used diagnostic
imaging tools to detect neurodegenerative disease. Diagnostic image quality is a key factor …
imaging tools to detect neurodegenerative disease. Diagnostic image quality is a key factor …