AIMC Topic: Anisotropy

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Effective and comfortable chain-linking anchoring with anisotropic stiffness for soft wearable robots.

Scientific reports
This study presents a wearable robot equipped with a novel anchoring structure designed to improve both force transmission efficiency and user comfort. While soft wearable robots are inherently more comfortable than rigid exoskeletons, they often suf...

Toroidal indentation for measuring cell and tissue mechanical anisotropy.

Acta biomaterialia
Indentation-based mechanical tests are advantageous for measuring tissue and cell stiffness due to their simplicity and ability to probe samples non-destructively. Most commonly, spherical or pyramidal probes are used, and Hertzian analysis is applie...

Self-supervised suppression of MRI cardiac device artifacts based on multi-instance contrastive learning and anisotropic spatiotemporal transformer.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Cardiovascular implantable electronic devices (CIEDs) induce severe off-resonance artifacts in balanced steady-state free precession (bSSFP) cine MRI, limiting diagnostic utility for a growing patient population. While supervised and unpaired learnin...

Towards High-Quality MRI Reconstruction With Anisotropic Diffusion-Assisted Generative Adversarial Networks and Its Multi-Modal Images Extension.

IEEE journal of biomedical and health informatics
Recently, fast Magnetic Resonance Imaging reconstruction technology has emerged as a promising way to improve the clinical diagnostic experience by significantly reducing scan times. While existing studies have used Generative Adversarial Networks to...

Adaptive Vectorial Restoration from Dynamic Speckle Patterns Through Biological Scattering Media Based on Deep Learning.

Sensors (Basel, Switzerland)
Imaging technologies based on vector optical fields hold significant potential in the biomedical field, particularly for non-invasive scattering imaging of anisotropic biological tissues. However, the dynamic and anisotropic nature of biological tiss...

Constitutive neural networks for main pulmonary arteries: discovering the undiscovered.

Biomechanics and modeling in mechanobiology
Accurate modeling of cardiovascular tissues is crucial for understanding and predicting their behavior in various physiological and pathological conditions. In this study, we specifically focus on the pulmonary artery in the context of the Ross proce...

Super-resolution mapping of anisotropic tissue structure with diffusion MRI and deep learning.

Scientific reports
Diffusion magnetic resonance imaging (diffusion MRI) is widely employed to probe the diffusive motion of water molecules within the tissue. Numerous diseases and processes affecting the central nervous system can be detected and monitored via diffusi...

Shape Anisotropy-Dependent Leaking in Magnetic Neurons for Bio-Mimetic Neuromorphic Computing.

ACS nano
Spiking neural networks seek to emulate biological computation through interconnected artificial neuron and synapse devices. Spintronic neurons can leverage magnetization physics to mimic biological neuron functions, such as integration tied to magne...

Seismic anisotropy prediction using ML methods: A case study on an offshore carbonate oilfield.

PloS one
Estimating seismic anisotropy parameters, such as Thomson's parameters, is crucial for investigating fractured and finely layered geological media. However, many inversion methods rely on complex physical models with initial assumptions, leading to n...

Conditional generative diffusion deep learning for accelerated diffusion tensor and kurtosis imaging.

Magnetic resonance imaging
PURPOSE: The purpose of this study was to develop DiffDL, a generative diffusion probabilistic model designed to produce high-quality diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) metrics from a reduced set of diffusion-weighted...