AI Medical Compendium Topic:
Signal-To-Noise Ratio

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Temporally downsampled cerebral CT perfusion image restoration using deep residual learning.

International journal of computer assisted radiology and surgery
PURPOSE: Acute ischemic stroke is one of the most causes of death all over the world. Onset to treatment time is critical in stroke diagnosis and treatment. Considering the time consumption and high price of MR imaging, CT perfusion (CTP) imaging is ...

A Cascaded Convolutional Neural Network for Assessing Signal Quality of Dynamic ECG.

Computational and mathematical methods in medicine
Motion artifacts and myoelectrical noise are common issues complicating the collection and processing of dynamic electrocardiogram (ECG) signals. Recent signal quality studies have utilized a binary classification metric in which ECG samples are dete...

A smoothing neural network for minimization l-l in sparse signal reconstruction with measurement noises.

Neural networks : the official journal of the International Neural Network Society
This paper investigates a smoothing neural network (SNN) to solve a robust sparse signal reconstruction in compressed sensing (CS), where the objective function is nonsmooth l-norm and the feasible set satisfies an inequality of l-norm 2≥p...

An Effective LSTM Recurrent Network to Detect Arrhythmia on Imbalanced ECG Dataset.

Journal of healthcare engineering
To reduce the high mortality rate from cardiovascular disease (CVD), the electrocardiogram (ECG) beat plays a significant role in computer-aided arrhythmia diagnosis systems. However, the complex variations and imbalance of ECG beats make this a chal...

Two stage residual CNN for texture denoising and structure enhancement on low dose CT image.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: X-ray computed tomography (CT) plays an important role in modern medical science. Human health problems caused by CT radiation have attracted the attention of the academic community widely. Reducing radiation dose results in...

Progressive Sub-Band Residual-Learning Network for MR Image Super Resolution.

IEEE journal of biomedical and health informatics
High-resolution (HR) magnetic resonance images (MRI) provide more detailed information for clinical application. However, HR MRI is less available because of the longer scan time and lower signal-to-noise ratio. Spatial resolution is one of the key p...

Deep CovDenseSNN: A hierarchical event-driven dynamic framework with spiking neurons in noisy environment.

Neural networks : the official journal of the International Neural Network Society
Neurons in the brain use an event signal, termed spike, encode temporal information for neural computation. Spiking neural networks (SNNs) take this advantage to serve as biological relevant models. However, the effective encoding of sensory informat...

Image reconstruction for positron emission tomography based on patch-based regularization and dictionary learning.

Medical physics
PURPOSE: Positron emission tomography (PET) is an important tool for nuclear medical imaging. It has been widely used in clinical diagnosis, scientific research, and drug testing. PET is a kind of emission computed tomography. Its basic imaging princ...

Pixelwise Estimation of Signal-Dependent Image Noise Using Deep Residual Learning.

Computational intelligence and neuroscience
In traditional image denoising, noise level is an important scalar parameter which decides how much the input noisy image should be smoothed. Existing noise estimation methods often assume that the noise level is constant at every pixel. However, rea...