AIMC Topic: Signal-To-Noise Ratio

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Attention-Based Joint Training of Noise Suppression and Sound Event Detection for Noise-Robust Classification.

Sensors (Basel, Switzerland) Oct 9, 2021
Sound event detection (SED) recognizes the corresponding sound event of an incoming signal and estimates its temporal boundary. Although SED has been recently developed and used in various fields, achieving noise-robust SED in a real environment is t...
Neural Networks, Computer Sound Signal-To-Noise Ratio Speech Noise
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Feasibility evaluation of PET scan-time reduction for diagnosing amyloid-β levels in Alzheimer's disease patients using a deep-learning-based denoising algorithm.

Computers in biology and medicine Oct 4, 2021
PURPOSE: To shorten positron emission tomography (PET) scanning time in diagnosing amyloid-β levels thus increasing the workflow in centers involving Alzheimer's Disease (AD) patients.
Humans Positron-Emission Tomography Algorithms Signal-To-Noise Ratio Deep Learning Feasibility Studies Image Processing, Computer-Assisted Alzheimer Disease
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Adaptive investigation of the optical properties of polymer fibers from mixing noisy phase shifting microinterferograms using deep learning algorithms.

Microscopy research and technique Oct 1, 2021
In this article, an adaptive denoising method is suggested to accurate investigate the optical and structural features of polymeric fibers from noisy phase shifting microinterferograms. The mixed class of noise that may produce in the phase-shifting ...
Deep Learning Polymers Signal-To-Noise Ratio Neural Networks, Computer Algorithms
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Comparison of different deep learning architectures for synthetic CT generation from MR images.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Sep 29, 2021
PURPOSE: Among the different available methods for synthetic CT generation from MR images for the task of MR-guided radiation planning, the deep learning algorithms have and do outperform their conventional counterparts. In this study, we investigate...
Deep Learning Image Processing, Computer-Assisted Signal-To-Noise Ratio Magnetic Resonance Imaging Tomography, X-Ray Computed Male Humans
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Recovery of Ionospheric Signals Using Fully Convolutional DenseNet and Its Challenges.

Sensors (Basel, Switzerland) Sep 28, 2021
The technique of active ionospheric sounding by ionosondes requires sophisticated methods for the recovery of experimental data on ionograms. In this work, we applied an advanced algorithm of deep learning for the identification and classification of...
Neural Networks, Computer Algorithms Taiwan Signal-To-Noise Ratio
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A Novel Medical Image Denoising Method Based on Conditional Generative Adversarial Network.

Computational and mathematical methods in medicine Sep 28, 2021
Medical image quality is highly relative to clinical diagnosis and treatment, leading to a popular research topic of medical image denoising. Image denoising based on deep learning methods has attracted considerable attention owing to its excellent a...
Signal-To-Noise Ratio Computer Simulation Computational Biology Tomography, X-Ray Computed Algorithms Lung Humans Image Interpretation, Computer-Assisted Databases, Factual Deep Learning Neural Networks, Computer
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Imaging in focus: An introduction to denoising bioimages in the era of deep learning.

The international journal of biochemistry & cell biology Sep 20, 2021
Fluorescence microscopy enables the direct observation of previously hidden dynamic processes of life, allowing profound insights into mechanisms of health and disease. However, imaging of live samples is fundamentally limited by the toxicity of the ...
Microscopy, Fluorescence Signal-To-Noise Ratio Humans Deep Learning Algorithms Image Processing, Computer-Assisted Animals
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DMC-Fusion: Deep Multi-Cascade Fusion With Classifier-Based Feature Synthesis for Medical Multi-Modal Images.

IEEE journal of biomedical and health informatics Sep 3, 2021
Multi-modal medical image fusion is a challenging yet important task for precision diagnosis and surgical planning in clinical practice. Although single feature fusion strategy such as Densefuse has achieved inspiring performance, it tends to be not ...
Signal-To-Noise Ratio Normal Distribution Neural Networks, Computer Brain
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Learning a Deep CNN Denoising Approach Using Anatomical Prior Information Implemented With Attention Mechanism for Low-Dose CT Imaging on Clinical Patient Data From Multiple Anatomical Sites.

IEEE journal of biomedical and health informatics Sep 3, 2021
Dose reduction in computed tomography (CT) has gained considerable attention in clinical applications because it decreases radiation risks. However, a lower dose generates noise in low-dose computed tomography (LDCT) images. Previous deep learning (D...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Signal-To-Noise Ratio Research Design Tomography, X-Ray Computed
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Ambulatory Cardiovascular Monitoring Via a Machine-Learning-Assisted Textile Triboelectric Sensor.

Advanced materials (Deerfield Beach, Fla.) Aug 31, 2021
Wearable bioelectronics for continuous and reliable pulse wave monitoring against body motion and perspiration remains a great challenge and highly desired. Here, a low-cost, lightweight, and mechanically durable textile triboelectric sensor that can...
Textiles Humans Monitoring, Ambulatory Signal-To-Noise Ratio Wearable Electronic Devices Heart Machine Learning Mobile Applications Nanotubes, Carbon Cardiovascular Diseases Blood Pressure
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