AIMC Topic: Signal-To-Noise Ratio

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Wavelet-Improved Score-Based Generative Model for Medical Imaging.

IEEE transactions on medical imaging Mar 5, 2024
The score-based generative model (SGM) has demonstrated remarkable performance in addressing challenging under-determined inverse problems in medical imaging. However, acquiring high-quality training datasets for these models remains a formidable tas...
Neural Networks, Computer Algorithms Magnetic Resonance Imaging Artifacts Signal-To-Noise Ratio Tomography, X-Ray Computed Image Processing, Computer-Assisted
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Colorful image reconstruction from neuromorphic event cameras with biologically inspired deep color fusion neural networks.

Bioinspiration & biomimetics Mar 4, 2024
Neuromorphic event-based cameras communicate transients in luminance instead of frames, providing visual information with a fine temporal resolution, high dynamic range and high signal-to-noise ratio. Enriching event data with color information allow...
Signal-To-Noise Ratio Neural Networks, Computer Image Processing, Computer-Assisted Equipment Design
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Coupling speckle noise suppression with image classification for deep-learning-aided ultrasound diagnosis.

Physics in medicine and biology Mar 4, 2024
. During deep-learning-aided (DL-aided) ultrasound (US) diagnosis, US image classification is a foundational task. Due to the existence of serious speckle noise in US images, the performance of DL models may be degraded. Pre-denoising US images befor...
Wavelet Analysis Image Enhancement Signal-To-Noise Ratio Algorithms Ultrasonography Deep Learning Image Processing, Computer-Assisted
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Recent developments in denoising medical images using deep learning: An overview of models, techniques, and challenges.

Micron (Oxford, England : 1993) Mar 2, 2024
Medical imaging plays a critical role in diagnosing and treating various medical conditions. However, interpreting medical images can be challenging even for expert clinicians, as they are often degraded by noise and artifacts that can hinder the acc...
Artificial Intelligence Algorithms Deep Learning Humans Neural Networks, Computer Image Processing, Computer-Assisted Signal-To-Noise Ratio
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A Hybrid Framework of Dual-Domain Signal Restoration and Multi-depth Feature Reinforcement for Low-Dose Lung CT Denoising.

Journal of imaging informatics in medicine Feb 29, 2024
Low-dose computer tomography (LDCT) has been widely used in medical diagnosis. Various denoising methods have been presented to remove noise in LDCT scans. However, existing methods cannot achieve satisfactory results due to the difficulties in (1) d...
Humans Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Tomography, X-Ray Computed Radiation Dosage Lung Signal-To-Noise Ratio
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Learning CT-free attenuation-corrected total-body PET images through deep learning.

European radiology Feb 15, 2024
OBJECTIVES: Total-body PET/CT scanners with long axial fields of view have enabled unprecedented image quality and quantitative accuracy. However, the ionizing radiation from CT is a major issue in PET imaging, which is more evident with reduced radi...
Humans Female Deep Learning Image Processing, Computer-Assisted Signal-To-Noise Ratio Whole Body Imaging Adult Positron Emission Tomography Computed Tomography Aged Male Young Adult Middle Aged
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A Review of deep learning methods for denoising of medical low-dose CT images.

Computers in biology and medicine Feb 15, 2024
To prevent patients from being exposed to excess of radiation in CT imaging, the most common solution is to decrease the radiation dose by reducing the X-ray, and thus the quality of the resulting low-dose CT images (LDCT) is degraded, as evidenced b...
Image Processing, Computer-Assisted Benchmarking Signal-To-Noise Ratio Tomography, X-Ray Computed Deep Learning Humans Algorithms
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Improved image quality in contrast-enhanced 3D-T1 weighted sequence by compressed sensing-based deep-learning reconstruction for the evaluation of head and neck.

Magnetic resonance imaging Feb 9, 2024
PURPOSE: To assess the utility of deep learning (DL)-based image reconstruction with the combination of compressed sensing (CS) denoising cycle by comparing images reconstructed by conventional CS-based method without DL in fat-suppressed (Fs)-contra...
Artifacts Signal-To-Noise Ratio Muscles Deep Learning Magnetic Resonance Imaging Humans Retrospective Studies
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Deep learning-based diffusion tensor image generation model: a proof-of-concept study.

Scientific reports Feb 5, 2024
This study created an image-to-image translation model that synthesizes diffusion tensor images (DTI) from conventional diffusion weighted images, and validated the similarities between the original and synthetic DTI. Thirty-two healthy volunteers we...
Diffusion Magnetic Resonance Imaging Corpus Callosum Internal Capsule Signal-To-Noise Ratio White Matter Humans Deep Learning
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Deep Learning-Based Reconstruction Improves the Image Quality of Low-Dose CT Colonography.

Academic radiology Jan 29, 2024
RATIONALE AND OBJECTIVES: To evaluate the image quality of low-dose CT colonography (CTC) using deep learning-based reconstruction (DLR) compared to iterative reconstruction (IR).
Signal-To-Noise Ratio Colonography, Computed Tomographic Middle Aged Adult Humans Radiographic Image Interpretation, Computer-Assisted Body Mass Index Deep Learning Radiation Dosage Female Male
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