AIMC Topic: Signal-To-Noise Ratio

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Utilizing deep learning techniques to improve image quality and noise reduction in preclinical low-dose PET images in the sinogram domain.

Medical physics Nov 15, 2023
BACKGROUND: Low-dose positron emission tomography (LD-PET) imaging is commonly employed in preclinical research to minimize radiation exposure to animal subjects. However, LD-PET images often exhibit poor quality and high noise levels due to the low ...
Positron-Emission Tomography Signal-To-Noise Ratio Rats Radiography Humans Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Animals
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Cross-Domain Unpaired Learning for Low-Dose CT Imaging.

IEEE journal of biomedical and health informatics Nov 7, 2023
Supervised deep-learning techniques with paired training datasets have been widely studied for low-dose computed tomography (LDCT) imaging with excellent performance. However, the paired training datasets are usually difficult to obtain in clinical r...
Humans Deep Learning Image Processing, Computer-Assisted Signal-To-Noise Ratio Algorithms Tomography, X-Ray Computed
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Evaluation of a Deep Learning Reconstruction for High-Quality T2-Weighted Breast Magnetic Resonance Imaging.

Tomography (Ann Arbor, Mich.) Oct 18, 2023
Deep learning (DL) reconstruction techniques to improve MR image quality are becoming commercially available with the hope that they will be applicable to multiple imaging application sites and acquisition protocols. However, before clinical implemen...
Humans Retrospective Studies Breast Signal-To-Noise Ratio Deep Learning Magnetic Resonance Imaging
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Reducing the risk of hallucinations with interpretable deep learning models for low-dose CT denoising: comparative performance analysis.

Physics in medicine and biology Oct 5, 2023
Reducing CT radiation dose is an often proposed measure to enhance patient safety, which, however results in increased image noise, translating into degradation of clinical image quality. Several deep learning methods have been proposed for low-dose ...
Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Radiation Dosage Signal-To-Noise Ratio Humans
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Preclinical validation of a novel deep learning-based metal artifact correction algorithm for orthopedic CT imaging.

Journal of applied clinical medical physics Oct 3, 2023
PURPOSE: To validate a novel deep learning-based metal artifact correction (MAC) algorithm for CT, namely, AI-MAC, in preclinical setting with comparison to conventional MAC and virtual monochromatic imaging (VMI) technique.
Signal-To-Noise Ratio Radiographic Image Interpretation, Computer-Assisted Artifacts Algorithms Retrospective Studies Deep Learning Tomography, X-Ray Computed Humans Metals
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Deep learning for fast denoising filtering in ultrasound localization microscopy.

Physics in medicine and biology Oct 2, 2023
Addition of a denoising filter step in ultrasound localization microscopy (ULM) has been shown to effectively reduce the error localizations of microbubbles (MBs) and achieve resolution improvement for super-resolution ultrasound (SR-US) imaging. How...
Neural Networks, Computer Animals Deep Learning Ultrasonography Microscopy Rabbits Image Processing, Computer-Assisted Signal-To-Noise Ratio
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A despeckling method for ultrasound images utilizing content-aware prior and attention-driven techniques.

Computers in biology and medicine Sep 25, 2023
The despeckling of ultrasound images contributes to the enhancement of image quality and facilitates precise treatment of conditions such as tumor cancers. However, the use of existing methods for eliminating speckle noise can cause the loss of image...
Breast Neoplasms Algorithms Ultrasonography Image Interpretation, Computer-Assisted Humans Female Image Processing, Computer-Assisted Signal-To-Noise Ratio Neural Networks, Computer
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Deep learning-based ultra-fast identification of Raman spectra with low signal-to-noise ratio.

Journal of biophotonics Sep 19, 2023
Ensuring the correct use of cell lines is crucial to obtaining reliable experimental results and avoiding unnecessary waste of resources. Raman spectroscopy has been confirmed to be able to identify cell lines, but the collection time is usually 10-3...
Deep Learning Spectrum Analysis, Raman Signal-To-Noise Ratio Cell Line Neural Networks, Computer
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Statistically unbiased prediction enables accurate denoising of voltage imaging data.

Nature methods Sep 18, 2023
Here we report SUPPORT (statistically unbiased prediction utilizing spatiotemporal information in imaging data), a self-supervised learning method for removing Poisson-Gaussian noise in voltage imaging data. SUPPORT is based on the insight that a pix...
Microscopy Signal-To-Noise Ratio Normal Distribution Neural Networks, Computer Image Processing, Computer-Assisted
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Comparison of convolutional-neural-networks-based method and LCModel on the quantification of in vivo magnetic resonance spectroscopy.

Magma (New York, N.Y.) Sep 15, 2023
BACKGROUND: Quantification of metabolites concentrations in institutional unit (IU) is important for inter-subject and long-term comparisons in the applications of magnetic resonance spectroscopy (MRS). Recently, deep learning (DL) algorithms have fo...
Signal-To-Noise Ratio Algorithms Magnetic Resonance Spectroscopy Male Brain Aspartic Acid Young Adult Deep Learning Female Humans Linear Models Adult Neural Networks, Computer
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