AIMC Topic: Signal-To-Noise Ratio

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Denoising of high-resolution 3D UTE-MR angiogram data using lightweight and efficient convolutional neural networks.

Magnetic resonance imaging
High-resolution magnetic resonance angiography (∼ 50 μm MRA) data plays a critical role in the accurate diagnosis of various vascular disorders. However, it is very challenging to acquire, and it is susceptible to artifacts and noise which limits its...

Accelerating prostate rs-EPI DWI with deep learning: Halving scan time, enhancing image quality, and validating in vivo.

Magnetic resonance imaging
OBJECTIVES: This study aims to evaluate the feasibility and effectiveness of deep learning-based super-resolution techniques to reduce scan time while preserving image quality in high-resolution prostate diffusion-weighted imaging (DWI) with readout-...

Groupwise image registration with edge-based loss for low-SNR cardiac MRI.

Magnetic resonance in medicine
PURPOSE: The purpose of this study is to perform image registration and averaging of multiple free-breathing single-shot cardiac images, where the individual images may have a low signal-to-noise ratio (SNR).

Can super resolution via deep learning improve classification accuracy in dental radiography?

Dento maxillo facial radiology
OBJECTIVES: Deep learning-driven super resolution (SR) aims to enhance the quality and resolution of images, offering potential benefits in dental imaging. Although extensive research has focused on deep learning based dental classification tasks, th...

Deep Learning-Based Saturation Compensation for High Dynamic Range Multispectral Fluorescence Lifetime Imaging.

IEEE transactions on bio-medical engineering
In multispectral fluorescence lifetime imaging (FLIm), achieving consistent imaging quality across all spectral channels is crucial for accurately identifying a wide range of fluorophores. However, these essential measurements are frequently compromi...

Reconstructing Super-Resolution Raman Spectral Image Using a Generative Adversarial Network-Based Algorithm.

Analytical chemistry
Raman imaging utilizes molecular fingerprint information to visualize the spatial distribution of a substance within the scanned area. Subject to its scanning mechanism, it usually costs a prolonged data acquisition duration for achieving high-resolu...

A modular deep learning pipeline for enhanced plane-wave beamforming and B-mode image quality.

Medical physics
BACKGROUND: In ultrasound imaging using plane-wave (PW) techniques, image quality and contrast often suffer, especially when examining anechoic structures. Traditional beamforming methods like Delay-and-Sum or coherent PW compounding face limitations...

Self-Supervised Optimization of RF Data Coherence for Improving Breast Reflection UCT Reconstruction.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
The reflection ultrasound computed tomography (UCT) is gaining prominence as an essential instrument for breast cancer screening. However, reflection UCT quality is often compromised by the variability in sound speed across breast tissue. Traditional...

Accelerating Diffusion: Task-Optimized latent diffusion models for rapid CT denoising.

Computers in biology and medicine
Computed tomography (CT) systems are indispensable for diagnostics but pose risks due to radiation exposure. Low-dose CT (LDCT) mitigates these risks but introduces noise and artifacts that compromise diagnostic accuracy. While deep learning methods,...