AIMC Topic: Signal-To-Noise Ratio

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Learned spatiotemporal correlation priors for CEST image denoising using incorporated global-spectral convolution neural network.

Magnetic resonance in medicine Jun 18, 2023
PURPOSE: To develop a deep learning-based method, dubbed Denoising CEST Network (DECENT), to fully exploit the spatiotemporal correlation prior to CEST image denoising.
Computer Simulation Animals Neural Networks, Computer Algorithms Signal-To-Noise Ratio Phantoms, Imaging Image Processing, Computer-Assisted Mice Humans
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Denoising single MR spectra by deep learning: Miracle or mirage?

Magnetic resonance in medicine Jun 18, 2023
PURPOSE: The inherently poor SNR of MRS measurements presents a significant hurdle to its clinical application. Denoising by machine or deep learning (DL) was proposed as a remedy. It is investigated whether such denoising leads to lower estimate unc...
Humans Signal-To-Noise Ratio Neural Networks, Computer Brain Deep Learning Image Processing, Computer-Assisted
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Denoising Tc-99m DMSA images using Denoising Convolutional Neural Network with comparison to a Block Matching Filter.

Nuclear medicine communications Jun 5, 2023
INTRODUCTION: A DnCNN for image denoising trained with natural images is available in MATLAB. For Tc-99m DMSA images, any loss of clinical details during the denoising process will have serious consequences since denoised image is to be used for diag...
Signal-To-Noise Ratio Technetium Tc 99m Dimercaptosuccinic Acid Image Processing, Computer-Assisted Cicatrix Humans Neural Networks, Computer Imaging, Three-Dimensional
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Noise Suppression With Similarity-Based Self-Supervised Deep Learning.

IEEE transactions on medical imaging Jun 1, 2023
Image denoising is a prerequisite for downstream tasks in many fields. Low-dose and photon-counting computed tomography (CT) denoising can optimize diagnostic performance at minimized radiation dose. Supervised deep denoising methods are popular but ...
Image Processing, Computer-Assisted Signal-To-Noise Ratio Tomography, X-Ray Computed Photons Deep Learning
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Electromagnetic interference elimination via active sensing and deep learning prediction for radiofrequency shielding-free MRI.

NMR in biomedicine May 28, 2023
At present, MRI scans are typically performed inside fully enclosed radiofrequency (RF) shielding rooms, posing stringent installation requirements and causing patient discomfort. We aim to eliminate electromagnetic interference (EMI) for MRI with no...
Radio Waves Deep Learning Magnetic Resonance Imaging Phantoms, Imaging Electromagnetic Fields Humans Signal-To-Noise Ratio
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AI-assisted compressed sensing and parallel imaging sequences for MRI of patients with nasopharyngeal carcinoma: comparison of their capabilities in terms of examination time and image quality.

European radiology May 23, 2023
OBJECTIVE: To compare examination time and image quality between artificial intelligence (AI)-assisted compressed sensing (ACS) technique and parallel imaging (PI) technique in MRI of patients with nasopharyngeal carcinoma (NPC).
Nasopharyngeal Neoplasms Magnetic Resonance Imaging Signal-To-Noise Ratio Artifacts Nasopharyngeal Carcinoma Humans Artificial Intelligence
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Deep Learning-Accelerated Liver Diffusion-Weighted Imaging: Intraindividual Comparison and Additional Phantom Study of Free-Breathing and Respiratory-Triggering Acquisitions.

Investigative radiology May 19, 2023
OBJECTIVES: Deep learning-reconstructed diffusion-weighted imaging (DL-DWI) is an emerging promising time-efficient method for liver evaluation, but analyses regarding different motion compensation strategies are lacking. This study evaluated the qua...
Reproducibility of Results Deep Learning Humans Abdomen Diffusion Magnetic Resonance Imaging Respiration Signal-To-Noise Ratio Liver
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Unsupervised Cryo-EM Images Denoising and Clustering Based on Deep Convolutional Autoencoder and K-Means+.

IEEE transactions on medical imaging May 2, 2023
Cryo-electron microscopy (cryo-EM) is a widely used structural determination technique. Because of the extremely low signal-to-noise ratio (SNR) of images captured by cryo-EM, clustering single-particle cryo-EM images with high accuracy is challengin...
Cluster Analysis Signal-To-Noise Ratio Cryoelectron Microscopy Reproducibility of Results Image Processing, Computer-Assisted Neural Networks, Computer
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Deep Learning Model to Denoise Luminescence Images of Silicon Solar Cells.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Apr 24, 2023
Luminescence imaging is widely used to identify spatial defects and extract key electrical parameters of photovoltaic devices. To reliably identify defects, high-quality images are desirable; however, acquiring such images implies a higher cost or lo...
Luminescence Signal-To-Noise Ratio Algorithms Silicon Deep Learning
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Self-supervised structural similarity-based convolutional neural network for cardiac diffusion tensor image denoising.

Medical physics Apr 17, 2023
BACKGROUND: Diffusion tensor imaging (DTI) is a promising technique for non-invasively investigating the myocardial fiber structures of human heart. However, low signal-to-noise ratio (SNR) has been a major limit of cardiac DTI to prevent us from det...
Signal-To-Noise Ratio Humans Diffusion Tensor Imaging Neural Networks, Computer Image Processing, Computer-Assisted Algorithms Heart
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