Results 231 to 240 of about 92,088 (287)

Denoising Method for NV-Center Fluorescence Signals Based on MPA-VMD Combined with Wavelet Thresholding. [PDF]

Micromachines (Basel)
He Y, Li X, Li Z, Guo H, Wen HF, Tang J, Liu J.   +6 more
europepmc   +1 more source

Advances in vital‐sign prediction and early‐warning models for underground coal mine workers integrating environmental factors

Deep Underground Science and Engineering, EarlyView.
This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu, Dawei Cui, Yingjie Liu, Yuntao Liang, Yue Zhang   +4 more
wiley   +1 more source

MEPrep: A robust pipeline for multi-echo fMRI denoising and preprocessing. [PDF]

Imaging Neurosci (Camb)
Wang Z, Liu F, Marsh R, Patel GH, Grinband J.   +4 more
europepmc   +1 more source

Distinct thalamic functional connectivity and volume patterns across focal epilepsies in children: A multimodal neuroimaging study

Epilepsia, EarlyView.
Abstract Objective The thalamus is a key hub in seizure propagation, and its nuclei are emerging targets for neuromodulation. However, the contributions of individual nuclei to epileptic networks remain unclear, particularly in children, who are less studied than adults.
Xiyu Feng, Aswin Chari, Maria H. Eriksson, Freya Prentice, Xiaosong He, Hua Xie, Leigh Sepeta, M. Zubair Tahir, Jonathan D. Clayden, Martin M. Tisdall, Torsten Baldeweg, Rory J. Piper   +11 more
wiley   +1 more source

Enhancing biomedical optical volumetric imaging via self-supervised orthogonal learning. [PDF]

Sci Adv
Gu Y, Wang Y, Xuan A, Wang J, Wang L, Zhang L, Li X, Wu Y, Zhang J, Lu Z, Dong B.   +10 more
europepmc   +1 more source

Enhanced 2D Spiral Cine DENSE MRI Using Low-Rank Denoising for Improved Apparent Signal-to-Noise Ratio, Spatial Resolution, Efficiency, Accuracy, and Accessibility. [PDF]

Magn Reson Med
Shih SF, Wu Y, Li S, Ming Z, Pogosyan A, Han F, Wu HH, Finn JP, Nguyen KL, Zhong X.   +9 more
europepmc   +1 more source

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RunDAE model: Running denoising autoencoder models for denoising ECG signals

Computers in Biology and Medicine, 2023
The denoising autoencoder (DAE) is commonly used to denoise bio-signals such as electrocardiogram (ECG) signals through dimensional reduction. Typically, the DAE model needs to be trained using correlated input segments such as QRS-aligned segments or long ECG segments. However, using long ECG segments as an input can result in a complex deep DAE model
Fars Samann, Thomas Schanze
openaire   +2 more sources

Schrödinger Equation Based ECG Signal Denoising

Chinese Journal of Physics, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Upadhyay, P., Upadhyay, S. K., Shukla, K. K.   +2 more
openaire   +2 more sources