AIMC Topic: Signal-To-Noise Ratio

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Improved quantitative parameter estimation for prostate T relaxometry using convolutional neural networks.

Magma (New York, N.Y.) Jul 23, 2024
OBJECTIVE: Quantitative parameter mapping conventionally relies on curve fitting techniques to estimate parameters from magnetic resonance image series. This study compares conventional curve fitting techniques to methods using neural networks (NN) f...
Prostatic Neoplasms Prostate Humans Image Interpretation, Computer-Assisted Neural Networks, Computer Signal-To-Noise Ratio Reproducibility of Results Algorithms Male Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Utility of Thin-slice Fat-suppressed Single-shot T2-weighted MR Imaging with Deep Learning Image Reconstruction as a Protocol for Evaluating the Pancreas.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Jul 21, 2024
PURPOSE: To compare the utility of thin-slice fat-suppressed single-shot T2-weighted imaging (T2WI) with deep learning image reconstruction (DLIR) and conventional fast spin-echo T2WI with DLIR for evaluating pancreatic protocol.
Pancreatic Neoplasms Image Interpretation, Computer-Assisted Pancreas Signal-To-Noise Ratio Image Processing, Computer-Assisted Contrast Media Magnetic Resonance Imaging Adipose Tissue Humans Retrospective Studies Gadolinium DTPA Female Aged Aged, 80 and over Male Middle Aged Deep Learning
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Deep learning image reconstruction for low-kiloelectron volt virtual monoenergetic images in abdominal dual-energy CT: medium strength provides higher lesion conspicuity.

Acta radiologica (Stockholm, Sweden : 1987) Jul 21, 2024
BACKGROUND: The best settings of deep learning image reconstruction (DLIR) algorithm for abdominal low-kiloelectron volt (keV) virtual monoenergetic imaging (VMI) have not been determined.
Algorithms Retrospective Studies Tomography, X-Ray Computed Female Radiographic Image Interpretation, Computer-Assisted Humans Signal-To-Noise Ratio Male Radiography, Abdominal Middle Aged Radiography, Dual-Energy Scanned Projection Aged Deep Learning Aged, 80 and over Image Processing, Computer-Assisted Adult
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Enhancing SNR in CEST imaging: A deep learning approach with a denoising convolutional autoencoder.

Magnetic resonance in medicine Jul 19, 2024
PURPOSE: To develop a SNR enhancement method for CEST imaging using a denoising convolutional autoencoder (DCAE) and compare its performance with state-of-the-art denoising methods.
Algorithms Animals Deep Learning Image Processing, Computer-Assisted Signal-To-Noise Ratio Mice Phantoms, Imaging Magnetic Resonance Imaging Principal Component Analysis
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Deep demosaicking convolution neural network and quantum wavelet transform-based image denoising.

Network (Bristol, England) Jul 11, 2024
Demosaicking is a popular scientific area that is being explored by a vast number of scientists. Current digital imaging technologies capture colour images with a single monochrome sensor. In addition, the colour images were captured using a sensor c...
Deep Learning Image Processing, Computer-Assisted Signal-To-Noise Ratio Wavelet Analysis Humans Neural Networks, Computer Algorithms
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Improving diagnostic confidence in low-dose dual-energy CTE with low energy level and deep learning reconstruction.

European journal of radiology Jul 10, 2024
OBJECTIVE: To demonstrate the value of using 50 keV virtual monochromatic images with deep learning image reconstruction (DLIR) in low-dose dual-energy CT enterography (CTE).
Middle Aged Deep Learning Radiographic Image Interpretation, Computer-Assisted Crohn Disease Aged Radiation Dosage Humans Adult Signal-To-Noise Ratio Prospective Studies Male Radiography, Dual-Energy Scanned Projection Tomography, X-Ray Computed Female
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Reconstructing Cancellous Bone From Down-Sampled Optical-Resolution Photoacoustic Microscopy Images With Deep Learning.

Ultrasound in medicine & biology Jul 7, 2024
OBJECTIVE: Bone diseases deteriorate the microstructure of bone tissue. Optical-resolution photoacoustic microscopy (OR-PAM) enables high spatial resolution of imaging bone tissues. However, the spatiotemporal trade-off limits the application of OR-P...
Cattle Image Processing, Computer-Assisted Microscopy Signal-To-Noise Ratio Photoacoustic Techniques Animals Cancellous Bone Deep Learning
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Fast, high-quality, and unshielded 0.2 T low-field mobile MRI using minimal hardware resources.

Magma (New York, N.Y.) Jul 5, 2024
OBJECTIVE: To propose a deep learning-based low-field mobile MRI strategy for fast, high-quality, unshielded imaging using minimal hardware resources.
Equipment Design Healthy Volunteers Signal-To-Noise Ratio Phantoms, Imaging Male Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Brain Female Adult Humans Algorithms
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Evaluation of 3D T1-weighted spoiled gradient echo MR image quality using artificial intelligence image reconstruction techniques in the pediatric brain.

Neuroradiology Jul 5, 2024
PURPOSE: To assess image quality and diagnostic confidence of 3D T1-weighted spoiled gradient echo (SPGR) MRI using artificial intelligence (AI) reconstruction.
Child, Preschool Child Imaging, Three-Dimensional Magnetic Resonance Imaging Female Male Adolescent Image Interpretation, Computer-Assisted Brain Diseases Signal-To-Noise Ratio Humans Artificial Intelligence Prospective Studies Brain
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Image quality of whole-body diffusion MR images comparing deep-learning accelerated and conventional sequences.

European radiology Jul 4, 2024
OBJECTIVES: To compare the image quality of deep learning accelerated whole-body (WB) with conventional diffusion sequences.
Female Aged Aged, 80 and over Adult Humans Artifacts Male Signal-To-Noise Ratio Middle Aged Whole Body Imaging Deep Learning Diffusion Magnetic Resonance Imaging
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