[HTML][HTML] What's new and what's next in diffusion MRI preprocessing
Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure
and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the …
and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the …
Improvement of image quality at CT and MRI using deep learning
Deep learning has been developed by computer scientists. Here, we discuss techniques for
improving the image quality of diagnostic computed tomography and magnetic resonance …
improving the image quality of diagnostic computed tomography and magnetic resonance …
A parallel MR imaging method using multilayer perceptron
Purpose To reconstruct MR images from subsampled data, we propose a fast reconstruction
method using the multilayer perceptron (MLP) algorithm. Methods and materials We applied …
method using the multilayer perceptron (MLP) algorithm. Methods and materials We applied …
Noninterpretive uses of artificial intelligence in radiology
We deem a computer to exhibit artificial intelligence (AI) when it performs a task that would
normally require intelligent action by a human. Much of the recent excitement about AI in the …
normally require intelligent action by a human. Much of the recent excitement about AI in the …
Improvement of late gadolinium enhancement image quality using a deep learning–based reconstruction algorithm and its influence on myocardial scar quantification
N van der Velde, HC Hassing, BJ Bakker… - European …, 2021 - Springer
Objectives The aim of this study was to assess the effect of a deep learning (DL)–based
reconstruction algorithm on late gadolinium enhancement (LGE) image quality and to …
reconstruction algorithm on late gadolinium enhancement (LGE) image quality and to …
Reconstruction of multicontrast MR images through deep learning
Purpose Magnetic resonance (MR) imaging with a long scan time can lead to degraded
images due to patient motion, patient discomfort, and increased costs. For these reasons …
images due to patient motion, patient discomfort, and increased costs. For these reasons …
Non-thermal plasma and Fe2+ activated persulfate ignited degradation of aqueous crystal violet: degradation mechanism and artificial neural network modeling
J Chen, J Feng, S Lu, Z Shen, Y Du, L Peng… - Separation and …, 2018 - Elsevier
Degradation of aqueous crystal violet (CV) by non-thermal plasma combined with Fe 2+
activated persulfate (PS) was investigated. Compared with single Fe 2+ activated PS system …
activated persulfate (PS) was investigated. Compared with single Fe 2+ activated PS system …
Magnetic-susceptibility-dependent ratiometric probes for enhancing quantitative MRI
C Zhang, B Nan, J Xu, T Yang, L Xu, C Lu… - Nature Biomedical …, 2024 - nature.com
In magnetic resonance imaging (MRI), quantitative measurements of analytes are hindered
by difficulties in distinguishing the MRI signals of activation of the probe by the analyte from …
by difficulties in distinguishing the MRI signals of activation of the probe by the analyte from …
Applying artificial intelligence to mitigate effects of patient motion or other complicating factors on image quality
Artificial intelligence, particularly deep learning, offers several possibilities to improve the
quality or speed of image acquisition in magnetic resonance imaging (MRI). In this article …
quality or speed of image acquisition in magnetic resonance imaging (MRI). In this article …
Artificial intelligence and radiomics in pediatric molecular imaging
In the past decade, a new approach for quantitative analysis of medical images and
prognostic modelling has emerged. Defined as the extraction and analysis of a large …
prognostic modelling has emerged. Defined as the extraction and analysis of a large …