AIMC Topic: Anisotropy

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A Highly Multi-Stable Meta-Structure via Anisotropy for Large and Reversible Shape Transformation.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Shape transformation offers the possibility of realizing devices whose 3D shape can be altered to adapt to different environments. Many applications would profit from reversible and actively controllable shape transformation together with a self-lock...

Deep learning enables reference-free isotropic super-resolution for volumetric fluorescence microscopy.

Nature communications
Volumetric imaging by fluorescence microscopy is often limited by anisotropic spatial resolution, in which the axial resolution is inferior to the lateral resolution. To address this problem, we present a deep-learning-enabled unsupervised super-reso...

Phase function estimation from a diffuse optical image via deep learning.

Physics in medicine and biology
The phase function is a key element of a light propagation model for Monte Carlo (MC) simulation, which is usually fitted with an analytic function with associated parameters. In recent years, machine learning methods were reported to estimate the pa...

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

Molecular biology of the cell
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...

Left-Handed or Right-Handed? Determinants of the Chirality of Helically Deformable Soft Actuators.

Soft robotics
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...

Can DXA image-based deep learning model predict the anisotropic elastic behavior of trabecular bone?

Journal of the mechanical behavior of biomedical materials
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...

Deep learning-based parameter estimation in fetal diffusion-weighted MRI.

NeuroImage
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...

SuperDTI: Ultrafast DTI and fiber tractography with deep learning.

Magnetic resonance in medicine
PURPOSE: To develop a deep learning-based reconstruction framework for ultrafast and robust diffusion tensor imaging and fiber tractography.

Cartilage structure increases swimming efficiency of underwater robots.

Scientific reports
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...

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
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...