AIMC Topic: Anisotropy

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On the application of hybrid deep 3D convolutional neural network algorithms for predicting the micromechanics of brain white matter.

Computer methods and programs in biomedicine Aug 22, 2024
BACKGROUND: Material characterization of brain white matter (BWM) is difficult due to the anisotropy inherent to the three-dimensional microstructure and the various interactions between heterogeneous brain-tissue (axon, myelin, and glia). Developing...
Brain Deep Learning Algorithms Finite Element Analysis Anisotropy White Matter Imaging, Three-Dimensional Neural Networks, Computer Humans
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Ultrafast diffusion tensor imaging based on deep learning and multi-slice information sharing.

Physics in medicine and biology Jan 30, 2024
. Diffusion tensor imaging (DTI) is excellent for non-invasively quantifying tissue microstructure. Theoretically DTI can be achieved with six different diffusion weighted images and one reference image, but the tensor estimation accuracy is poor in ...
Humans Diffusion Magnetic Resonance Imaging Anisotropy Deep Learning Algorithms Diffusion Tensor Imaging
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Cellstitch: 3D cellular anisotropic image segmentation via optimal transport.

BMC bioinformatics Dec 15, 2023
BACKGROUND: Spatial mapping of transcriptional states provides valuable biological insights into cellular functions and interactions in the context of the tissue. Accurate 3D cell segmentation is a critical step in the analysis of this data towards u...
Anisotropy Neural Networks, Computer Image Processing, Computer-Assisted Imaging, Three-Dimensional
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Learnable PM diffusion coefficients and reformative coordinate attention network for low dose CT denoising.

Physics in medicine and biology Dec 11, 2023
Various deep learning methods have recently been used for low dose CT (LDCT) denoising. Aggressive denoising may destroy the edge and fine anatomical structures of CT images. Therefore a key issue in LDCT denoising tasks is the difficulty of balancin...
Neural Networks, Computer Tomography, X-Ray Computed Anisotropy Signal-To-Noise Ratio Image Processing, Computer-Assisted
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A strategy to formulate data-driven constitutive models from random multiaxial experiments.

Scientific reports Dec 23, 2022
We present a test technique and an accompanying computational framework to obtain data-driven, surrogate constitutive models that capture the response of isotropic, elastic-plastic materials loaded in-plane stress by combined normal and shear stresse...
Finite Element Analysis Anisotropy Neural Networks, Computer Tensile Strength Stress, Mechanical Plastics
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Anisotropic SpiralNet for 3D Shape Completion and Denoising.

Sensors (Basel, Switzerland) Aug 27, 2022
Three-dimensional mesh post-processing is an important task because low-precision hardware and a poor capture environment will inevitably lead to unordered point clouds with unwanted noise and holes that should be suitably corrected while preserving ...
Head Neural Networks, Computer Anisotropy Artifacts
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Synergy of Spin-Orbit Torque and Built-In Field in Magnetic Tunnel Junctions with Tilted Magnetic Anisotropy: Toward Tunable and Reliable Spintronic Neurons.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Aug 4, 2022
Owing to programmable nonlinear dynamics, magnetic domain wall (DW)-based devices can be configured to function as spintronic neurons, promising to execute sophisticated tasks as a human brain. Developing energy-efficient, CMOS compatible, reliable, ...
Humans Magnetic Phenomena Neural Networks, Computer Anisotropy Torque Synapses Neurons
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A Highly Multi-Stable Meta-Structure via Anisotropy for Large and Reversible Shape Transformation.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Jul 21, 2022
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...
Locomotion Anisotropy Robotics
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Deep learning enables reference-free isotropic super-resolution for volumetric fluorescence microscopy.

Nature communications Jun 8, 2022
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...
Deep Learning Imaging, Three-Dimensional Anisotropy Microscopy, Fluorescence
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Phase function estimation from a diffuse optical image via deep learning.

Physics in medicine and biology Mar 25, 2022
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...
Monte Carlo Method Computer Simulation Anisotropy Neural Networks, Computer Deep Learning
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