AIMC Topic: Image Enhancement

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Deep Learning Automated Background Phase Error Correction for Abdominopelvic 4D Flow MRI.

Radiology Nov 30, 2021
Background Four-dimensional (4D) flow MRI has the potential to provide hemodynamic insights for a variety of abdominopelvic vascular diseases, but its clinical utility is currently impaired by background phase error, which can be challenging to corre...
Middle Aged Hemodynamics Deep Learning Image Interpretation, Computer-Assisted Humans Image Enhancement Retrospective Studies Blood Flow Velocity Male Abdomen Magnetic Resonance Imaging Vascular Diseases
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Extending Camera's Capabilities in Low Light Conditions Based on LIP Enhancement Coupled with CNN Denoising.

Sensors (Basel, Switzerland) Nov 27, 2021
Using a sensor in variable lighting conditions, especially very low-light conditions, requires the application of image enhancement followed by denoising to retrieve correct information. The limits of such a process are explored in the present paper,...
Humans Neural Networks, Computer Reproducibility of Results Image Processing, Computer-Assisted Image Enhancement Signal-To-Noise Ratio
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Image Enhancement Model Based on Deep Learning Applied to the Ureteroscopic Diagnosis of Ureteral Stones during Pregnancy.

Computational and mathematical methods in medicine Oct 29, 2021
OBJECTIVE: To explore the image enhancement model based on deep learning on the effect of ureteroscopy with double J tube placement and drainage on ureteral stones during pregnancy. We compare the clinical effect of ureteroscopy with double J tube pl...
Deep Learning Lithotripsy Pregnancy Models, Statistical Ultrasonography Image Enhancement Humans Female Artifacts Computational Biology Ureteroscopy Neural Networks, Computer Diagnosis, Computer-Assisted Pregnancy Complications Ureteral Calculi
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Imaging depth adaptive resolution enhancement for optical coherence tomography via deep neural network with external attention.

Physics in medicine and biology Sep 24, 2021
Optical coherence tomography (OCT) is a promising non-invasive imaging technique that owns many biomedical applications. In this paper, a deep neural network is proposed for enhancing the spatial resolution of OCTimages. Different from the previous r...
Neural Networks, Computer Tomography, Optical Coherence Retina Image Enhancement
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Single image mixed dehazing method based on numerical iterative model and DehazeNet.

PloS one Jul 30, 2021
As one of the most common adverse weather phenomena, haze has caused detrimental effects on many computer vision systems. To eliminate the effect of haze, in the field of image processing, image dehazing has been studied intensively, and many advance...
Artificial Intelligence Models, Theoretical Image Enhancement
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Low-Light Image Enhancement Based on Multi-Path Interaction.

Sensors (Basel, Switzerland) Jul 22, 2021
Due to the non-uniform illumination conditions, images captured by sensors often suffer from uneven brightness, low contrast and noise. In order to improve the quality of the image, in this paper, a multi-path interaction network is proposed to enhan...
Image Enhancement Image Processing, Computer-Assisted Noise Lighting Neural Networks, Computer
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Toward Replacing Late Gadolinium Enhancement With Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy.

Circulation Jul 7, 2021
BACKGROUND: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging is the gold standard for noninvasive myocardial tissue characterization but requires intravenous contrast agent administration. It is highly desired to deve...
Humans Artificial Intelligence Magnetic Resonance Imaging Cardiomyopathy, Hypertrophic Gadolinium Deep Learning Image Processing, Computer-Assisted Contrast Media Image Enhancement
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Artificial intelligence for the detection of gastric precancerous conditions using image-enhanced endoscopy: What kind of abilities are required for application in real-world clinical practice?

Gastrointestinal endoscopy Jun 25, 2021
Humans Artificial Intelligence Endoscopy Image Enhancement Precancerous Conditions
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Single-breath-hold T2WI liver MRI with deep learning-based reconstruction: A clinical feasibility study in comparison to conventional multi-breath-hold T2WI liver MRI.

Magnetic resonance imaging Jun 18, 2021
OBJECTIVE: To investigate the clinical feasibility of single-breath-hold (SBH) T2-weighted (T2WI) liver MRI with deep learning-based reconstruction in the evaluation of image quality and lesion delineation, compared with conventional multi-breath-hol...
Liver Feasibility Studies Artifacts Image Enhancement Liver Diseases Deep Learning Liver Neoplasms Magnetic Resonance Imaging Humans Adult
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Machine learning-based radiomic evaluation of treatment response prediction in glioblastoma.

Clinical radiology May 1, 2021
AIM: To investigate machine learning based models combining clinical, radiomic, and molecular information to distinguish between early true progression (tPD) and pseudoprogression (psPD) in patients with glioblastoma.
Brain Neoplasms Brain Retrospective Studies Male Female Middle Aged Chemoradiotherapy Adolescent Young Adult Humans Treatment Outcome Adult Machine Learning Glioblastoma Contrast Media Sensitivity and Specificity Image Interpretation, Computer-Assisted Magnetic Resonance Imaging Reproducibility of Results Image Enhancement Diagnosis, Differential Aged Predictive Value of Tests
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