AIMC Topic: Anisotropy

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DynaMorph: self-supervised learning of morphodynamic states of live cells.

Molecular biology of the cell Feb 9, 2022
A cell's shape and motion represent fundamental aspects of cell identity and can be highly predictive of function and pathology. However, automated analysis of the morphodynamic states remains challenging for most cell types, especially primary human...
Brain Supervised Machine Learning Anisotropy Humans
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Left-Handed or Right-Handed? Determinants of the Chirality of Helically Deformable Soft Actuators.

Soft robotics Sep 28, 2021
Helical curling and spiral structure are very common in nature, which inspire researchers to create various forms of helical configurations and actuators. The helically deformable actuators perform asymmetric deformations and show different chirality...
Finite Element Analysis Anisotropy Elastic Modulus Robotics
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Can DXA image-based deep learning model predict the anisotropic elastic behavior of trabecular bone?

Journal of the mechanical behavior of biomedical materials Sep 15, 2021
3D image-based finite element (FE) and bone volume fraction (BV/TV)/fabric tensor modeling techniques are currently used to determine the apparent stiffness tensor of trabecular bone for assessing its anisotropic elastic behavior. Inspired by the rec...
Humans Finite Element Analysis Bone Density X-Ray Microtomography Anisotropy Deep Learning Absorptiometry, Photon Cancellous Bone
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Deep learning-based parameter estimation in fetal diffusion-weighted MRI.

NeuroImage Aug 26, 2021
Diffusion-weighted magnetic resonance imaging (DW-MRI) of fetal brain is challenged by frequent fetal motion and signal to noise ratio that is much lower than non-fetal imaging. As a result, accurate and robust parameter estimation in fetal DW-MRI re...
Reproducibility of Results Deep Learning Neural Networks, Computer Infant, Newborn Infant, Premature Signal-To-Noise Ratio Fetus Image Processing, Computer-Assisted Motion Humans Diffusion Magnetic Resonance Imaging Gestational Age Anisotropy
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SuperDTI: Ultrafast DTI and fiber tractography with deep learning.

Magnetic resonance in medicine Jul 26, 2021
PURPOSE: To develop a deep learning-based reconstruction framework for ultrafast and robust diffusion tensor imaging and fiber tractography.
White Matter Diffusion Tensor Imaging Diffusion Magnetic Resonance Imaging Anisotropy Deep Learning Image Processing, Computer-Assisted Humans
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Cartilage structure increases swimming efficiency of underwater robots.

Scientific reports May 28, 2021
Underwater robots are useful for exploring valuable resources and marine life. Traditional underwater robots use screw propellers, which may be harmful to marine life. In contrast, robots that incorporate the swimming principles, morphologies, and so...
Skates, Fish Cartilage Biophysical Phenomena Robotics Biomechanical Phenomena Anisotropy Mechanical Phenomena Animals Equipment Design Animal Fins Swimming
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Deep Learning-based Noise Reduction for Fast Volume Diffusion Tensor Imaging: Assessing the Noise Reduction Effect and Reliability of Diffusion Metrics.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Sep 18, 2020
To assess the feasibility of a denoising approach with deep learning-based reconstruction (dDLR) for fast volume simultaneous multi-slice diffusion tensor imaging of the brain, noise reduction effects and the reliability of diffusion metrics were eva...
Deep Learning Image Processing, Computer-Assisted Diffusion Tensor Imaging Anisotropy Benchmarking Humans Reproducibility of Results
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Extracting diffusion tensor fractional anisotropy and mean diffusivity from 3-direction DWI scans using deep learning.

Magnetic resonance in medicine Aug 18, 2020
PURPOSE: To develop and evaluate machine-learning methods that reconstruct fractional anisotropy (FA) values and mean diffusivities (MD) from 3-direction diffusion MRI (dMRI) acquisitions.
Anisotropy Diffusion Magnetic Resonance Imaging Deep Learning Magnetic Resonance Imaging Diffusion Tensor Imaging Humans
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A deep learning-based method for improving reliability of multicenter diffusion kurtosis imaging with varied acquisition protocols.

Magnetic resonance imaging Aug 18, 2020
Multicenter magnetic resonance imaging is gaining more popularity in large-sample projects. Since both varying hardware and software across different centers cause unavoidable data heterogeneity across centers, its impact on reliability in study outc...
White Matter Humans Anisotropy Reproducibility of Results Deep Learning Male Image Processing, Computer-Assisted Female Diffusion Magnetic Resonance Imaging
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Anisotropic Gaussian kernel adaptive filtering by Lie-group dictionary learning.

PloS one Aug 14, 2020
The present paper proposes a novel kernel adaptive filtering algorithm, where each Gaussian kernel is parameterized by a center vector and a symmetric positive definite (SPD) precision matrix, which is regarded as a generalization of scalar width par...
Anisotropy Nonlinear Dynamics Machine Learning Normal Distribution Algorithms
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