AIMC Topic: Image Enhancement

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Improvement of late gadolinium enhancement image quality using a deep learning-based reconstruction algorithm and its influence on myocardial scar quantification.

European radiology Nov 21, 2020
OBJECTIVES: The aim of this study was to assess the effect of a deep learning (DL)-based reconstruction algorithm on late gadolinium enhancement (LGE) image quality and to evaluate its influence on scar quantification.
Algorithms Female Male Humans Cicatrix Myocardium Gadolinium Image Enhancement Deep Learning Contrast Media Magnetic Resonance Imaging
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Artificial Intelligence Applied to Breast MRI for Improved Diagnosis.

Radiology Oct 20, 2020
Background Recognition of salient MRI morphologic and kinetic features of various malignant tumor subtypes and benign diseases, either visually or with artificial intelligence (AI), allows radiologists to improve diagnoses that may improve patient tr...
Humans Reproducibility of Results Sensitivity and Specificity Breast Neoplasms Middle Aged Artificial Intelligence Retrospective Studies Female Contrast Media Magnetic Resonance Imaging Diagnosis, Differential Breast Image Interpretation, Computer-Assisted Image Enhancement
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Uncertainty modelling in deep learning for safer neuroimage enhancement: Demonstration in diffusion MRI.

NeuroImage Oct 9, 2020
Deep learning (DL) has shown great potential in medical image enhancement problems, such as super-resolution or image synthesis. However, to date, most existing approaches are based on deterministic models, neglecting the presence of different source...
Humans Brain Deep Learning Uncertainty Image Enhancement Diffusion Magnetic Resonance Imaging Diffusion Tensor Imaging Image Processing, Computer-Assisted Neuroimaging
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Improving Quantitative Magnetic Resonance Imaging Using Deep Learning.

Seminars in musculoskeletal radiology Sep 29, 2020
Deep learning methods have shown promising results for accelerating quantitative musculoskeletal (MSK) magnetic resonance imaging (MRI) for T2 and T1ρ relaxometry. These methods have been shown to improve musculoskeletal tissue segmentation on parame...
Image Interpretation, Computer-Assisted Humans Musculoskeletal Diseases Deep Learning Image Enhancement Contrast Media Magnetic Resonance Imaging
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Noise reduction with cross-tracer and cross-protocol deep transfer learning for low-dose PET.

Physics in medicine and biology Sep 14, 2020
Previous studies have demonstrated the feasibility of reducing noise with deep learning-based methods for low-dose fluorodeoxyglucose (FDG) positron emission tomography (PET). This work aimed to investigate the feasibility of noise reduction for trac...
Humans Deep Learning Positron-Emission Tomography Image Enhancement Radiation Dosage Signal-To-Noise Ratio
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Editorial Comment on "Diagnostic Accuracy of Quantitative Multicontrast 5-Minute Knee MRI Using Prospective Artificial Intelligence Image Quality Enhancement".

AJR. American journal of roentgenology Sep 9, 2020
Magnetic Resonance Imaging Image Enhancement Humans Artificial Intelligence Prospective Studies
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Value of MR-based radiomics in differentiating uveal melanoma from other intraocular masses in adults.

European journal of radiology Sep 8, 2020
PURPOSE: To assess the performance of machine learning (ML)-based magnetic resonance imaging (MRI) radiomics analysis for discriminating between uveal melanoma (UM) and other intraocular masses.
Image Enhancement Uveal Neoplasms Uveal Melanoma Contrast Media Magnetic Resonance Imaging Diagnosis, Differential Humans Eye Neoplasms Retrospective Studies Aged Female Logistic Models Young Adult Child Male Melanoma Adult Middle Aged Support Vector Machine ROC Curve Reproducibility of Results Adolescent
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High tissue contrast image synthesis via multistage attention-GAN: Application to segmenting brain MR scans.

Neural networks : the official journal of the International Neural Network Society Aug 18, 2020
Magnetic resonance imaging (MRI) presents a detailed image of the internal organs via a magnetic field. Given MRI's non-invasive advantage in repeated imaging, the low-contrast MR images in the target area make segmentation of tissue a challenging pr...
Humans Neural Networks, Computer Brain Attention Brain Neoplasms Image Enhancement Infant Magnetic Resonance Imaging
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Improving the Reliability of Pharmacokinetic Parameters at Dynamic Contrast-enhanced MRI in Astrocytomas: A Deep Learning Approach.

Radiology Aug 4, 2020
Background Pharmacokinetic (PK) parameters obtained from dynamic contrast agent-enhanced (DCE) MRI evaluates the microcirculation permeability of astrocytomas, but the unreliability from arterial input function (AIF) remains a challenge. Purpose To d...
Contrast Media Image Enhancement Astrocytoma Male Middle Aged Deep Learning Female Reproducibility of Results Brain Neoplasms Humans Retrospective Studies
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Attention-Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images.

Ultrasound in medicine & biology Jul 21, 2020
Incorporating human domain knowledge for breast tumor diagnosis is challenging because shape, boundary, curvature, intensity or other common medical priors vary significantly across patients and cannot be employed. This work proposes a new approach t...
Attention Deep Learning Humans Image Enhancement Models, Theoretical Female Ultrasonography, Mammary Breast Neoplasms
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