Results 51 to 60 of about 2,392 (180)

Cardiac MR Fingerprinting at 0.55T Using a Deep Image Prior for Joint T1, T2, and M0 Mapping

Journal of Magnetic Resonance Imaging, EarlyView.
ABSTRACT Background 0.55T systems offer unique advantages and may support expanded access to cardiac MRI. Purpose To assess the feasibility of 0.55T cardiac MR Fingerprinting (MRF), leveraging a deep image prior reconstruction to mitigate noise. Study Type Phantom and prospective in vivo assessment.
Zhongnan Liu, Zexuan Liu, Imran Rashid, Mauricio Stanzione Galizia, Christopher Scoma, William Truesdell, Prachi Agarwal, Nicole Seiberlich, Liyue Shen, Jesse Hamilton   +9 more
wiley   +1 more source

Real Color Image Denoising Using t-Product- Based Weighted Tensor Nuclear Norm Minimization

IEEE Access, 2019
Color images can be seen as third-order tensors with column, row and color modes. Considering two inherent characteristics of a color image including the non-local self-similarity (NSS) and the cross-channel correlation, we extract non-local similar ...
Min Liu, Xinggan Zhang, Lan Tang
doaj   +1 more source

Enhancing generalized spectral clustering with embedding Laplacian graph regularization

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang, Jian Yang, Bob Zhang, Yang Tang, Wenli Du, Bihan Wen   +5 more
wiley   +1 more source

Exploring Tensor-Based Optimization for Missing EEG Signal Recovery: A Comparative Study of Optimization Methods Across Different Tensor Decomposition Frameworks

IEEE Access
Electroencephalography (EEG) signals are frequently compromised by missing data due to electrode contact issues or subject movement. Tensor decomposition has emerged as a powerful technique for analyzing multidimensional EEG data.
Yue Zhang, Huanmin Ge, Chencheng Huang, Xinhua Su   +3 more
doaj   +1 more source

Tensor Changepoint Detection and Eigenbootstrap

Journal of Time Series Analysis, EarlyView.
ABSTRACT Tensor data consisting of multivariate outcomes over the items and across the subjects with longitudinal and cross‐sectional dependence are considered. A completely distribution‐free and tweaking‐parameter‐free detection procedure for changepoints at different locations is designed, which does not require training data.
Michal Pešta, Barbora Peštová, Martin Romaňák   +2 more
wiley   +1 more source

Robust Tensor Factorization for Color Image and Grayscale Video Recovery

IEEE Access, 2020
Low-rank tensor completion (LRTC) plays an important role in many fields, such as machine learning, computer vision, image processing, and mathematical theory.
Shiqiang Du, Yuqing Shi, Wenjin Hu, Weilan Wang, Jing Lian   +4 more
doaj   +1 more source

Application of Diffusion Tensor Imaging Parameters to Detect Change in Longitudinal Studies in Cerebral Small Vessel Disease. [PDF]

PLoS ONE, 2016
Cerebral small vessel disease (SVD) is the major cause of vascular cognitive impairment, resulting in significant disability and reduced quality of life.
Eva Anna Zeestraten, Philip Benjamin, Christian Lambert, Andrew John Lawrence, Owen Alan Williams, Robin Guy Morris, Thomas Richard Barrick, Hugh Stephen Markus   +7 more
doaj   +1 more source

The Contribution of White Matter Diffusion and Cortical Perfusion Pathology to Vascular Cognitive Impairment: A Multimode Imaging-Based Machine Learning Study

Frontiers in Aging Neuroscience, 2021
Widespread impairments in white matter and cerebrovascular integrity have been consistently implicated in the pathophysiology of patients with small vessel disease (SVD).
Yao Wang, Peiwen Lu, Yafeng Zhan, Xiaowei Wu, Yage Qiu, Zheng Wang, Qun Xu, Yan Zhou   +7 more
doaj   +1 more source

Tensor Decomposition Through Neural Architectures

Applied Sciences
Machine learning (ML) technologies are currently widely used in many domains of science and technology, to discover models that transform input data into output data.
Chady Ghnatios, Francisco Chinesta
doaj   +1 more source

The effect of the total small vessel disease burden on the structural brain network

Scientific Reports, 2018
Different cerebral small vessel disease (SVD) lesion types have been shown to disrupt structural brain network individually. Considering that they often coexist, we investigated the relation between their collective effect using the recently proposed ...
Xiaopei Xu, Kui Kai Lau, Yuen Kwun Wong, Henry K. F. Mak, Edward S. Hui   +4 more
doaj   +1 more source