AIMC Topic: Signal-To-Noise Ratio

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Automatic noise detection for ambulatory electrocardiogram in presence of ventricular arrhythmias through a machine learning approach.

Computers in biology and medicine Oct 23, 2024
Noise detection in ambulatory electrocardiography is investigated as a machine learning binary classification problem on a set of twelve noise indices. Ten of these noise indices are replicated from relevant scientific literature. Two novel noise ind...
Signal-To-Noise Ratio Tachycardia, Ventricular Electrocardiography, Ambulatory Arrhythmias, Cardiac Humans Machine Learning Signal Processing, Computer-Assisted
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Deep-Learning-Based Segmentation of Cells and Analysis (DL-SCAN).

Biomolecules Oct 23, 2024
With the recent surge in the development of highly selective probes, fluorescence microscopy has become one of the most widely used approaches to studying cellular properties and signaling in living cells and tissues. Traditionally, microscopy image ...
Software Brain Animals Deep Learning Calcium Sodium Signal-To-Noise Ratio Fluorescent Dyes Microscopy, Fluorescence Image Processing, Computer-Assisted Neurons Mice Astrocytes
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Deep-learning reconstruction enhances image quality of Adamkiewicz Artery in low-keV dual-energy CT.

Acta radiologica (Stockholm, Sweden : 1987) Oct 22, 2024
BACKGROUND: Low-keV virtual monoenergetic images (VMIs) of dual-energy computed tomography (CT) enhances iodine contrast for detecting small arteries like the Adamkiewicz artery (AKA), but image noise can be problematic. Deep-learning image reconstru...
Contrast Media Radiographic Image Interpretation, Computer-Assisted Spinal Cord Middle Aged Deep Learning Signal-To-Noise Ratio Computed Tomography Angiography Radiography, Dual-Energy Scanned Projection Retrospective Studies Female Aged Aged, 80 and over Adult Male Humans
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Deep plug-and-play MRI reconstruction based on multiple complementary priors.

Magnetic resonance imaging Oct 16, 2024
Magnetic resonance imaging (MRI) is widely used in clinical diagnosis as a safe, non-invasive, high-resolution medical imaging technology, but long scanning time has been a major challenge for this technology. The undersampling reconstruction method ...
Humans Neural Networks, Computer Algorithms Phantoms, Imaging Image Processing, Computer-Assisted Magnetic Resonance Imaging Brain Signal-To-Noise Ratio Deep Learning
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Signal processing for enhancing railway communication by integrating deep learning and adaptive equalization techniques.

PloS one Oct 11, 2024
With the increasing amount of data in railway communication system, the conventional wireless high-frequency communication technology cannot meet the requirements of modern communication and needs to be improved. In order to meet the requirements of ...
Wireless Technology Railroads Deep Learning Algorithms Signal Processing, Computer-Assisted Communication Signal-To-Noise Ratio
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Acoustic leak localization for water distribution network through time-delay-based deep learning approach.

Water research Oct 9, 2024
Water leakage within water distribution networks (WDNs) presents significant challenges, encompassing infrastructure damage, economic losses, and public health risks. Traditional methods for leak localization based on acoustic signals encounter inher...
Deep Learning Water Acoustics Signal-To-Noise Ratio Water Supply
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Deep Spatio-Temporal Network for Low-SNR Cryo-EM Movie Frame Enhancement.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2024
Cryo-EM in single particle analysis is known to have low SNR and requires to utilize several frames of the same particle sample to restore one high-quality image for visualizing that particle. However, the low SNR of cryo-EM movie and motion caused b...
Signal-To-Noise Ratio Cryoelectron Microscopy Algorithms Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer
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Deep Learning-Based Synthetic Computed Tomography for Low-Field Brain Magnetic Resonance-Guided Radiation Therapy.

International journal of radiation oncology, biology, physics Oct 1, 2024
PURPOSE: Magnetic resonance (MR)-guided radiation therapy enables online adaptation to address intra- and interfractional changes. To address the need of high-fidelity synthetic computed tomography (synCT) required for dose calculation, we developed ...
Tomography, X-Ray Computed Brain Neoplasms Deep Learning Humans Prospective Studies Brain Signal-To-Noise Ratio Radiotherapy Dosage Radiotherapy, Image-Guided Glioma Magnetic Resonance Imaging Radiotherapy Planning, Computer-Assisted
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Deep Neural Network-Based Empirical Mode Decomposition for Motor Imagery EEG Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Oct 1, 2024
Motor imagery refers to the brain's response during the mental simulation of physical activities, which can be detected through electroencephalogram (EEG) signals. However, EEG signals exhibit a low signal-to-noise ratio (SNR) due to various artifact...
Artifacts Signal-To-Noise Ratio Imagination Electroencephalography Signal Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms Deep Learning
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Reconstructing and analyzing the invariances of low-dose CT image denoising networks.

Medical physics Sep 30, 2024
BACKGROUND: Deep learning-based methods led to significant advancements in many areas of medical imaging, most of which are concerned with the reduction of artifacts caused by motion, scatter, or noise. However, with most neural networks being black ...
Signal-To-Noise Ratio Deep Learning Humans Image Processing, Computer-Assisted Neural Networks, Computer Radiation Dosage Tomography, X-Ray Computed
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