AIMC Topic: Image Enhancement
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Effectiveness of deep learning-based reconstruction for improvement of image quality and liver tumor detectability in the hepatobiliary phase of gadoxetic acid-enhanced magnetic resonance imaging.
Abdominal radiology (New York)
May 16, 2024
PURPOSE: To evaluate the effectiveness of deep learning-based reconstruction (DLR) in improving image quality and tumor detectability of isovoxel high-resolution breath-hold fat-suppressed T1-weighted imaging (HR-BH-FS-T1WI) in the hepatobiliary phas...
Voxel level dense prediction of acute stroke territory in DWI using deep learning segmentation models and image enhancement strategies.
Japanese journal of radiology
May 10, 2024
PURPOSE: To build a stroke territory classifier model in DWI by designing the problem as a multiclass segmentation task by defining each stroke territory as distinct segmentation targets and leveraging the guidance of voxel wise dense predictions.
Deep Learning Synthesis of White-Blood From Dark-Blood Late Gadolinium Enhancement Cardiac Magnetic Resonance.
Investigative radiology
May 1, 2024
OBJECTIVES: Dark-blood late gadolinium enhancement (DB-LGE) cardiac magnetic resonance has been proposed as an alternative to standard white-blood LGE (WB-LGE) imaging protocols to enhance scar-to-blood contrast without compromising scar-to-myocardiu...
Deep Learning-based Image Enhancement Techniques for Fast MRI in Neuroimaging.
Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Apr 27, 2024
Despite its superior soft tissue contrast and non-invasive nature, MRI requires long scan times due to its intrinsic signal acquisition principles, a main drawback which technological advancements in MRI have been focused on. In particular, scan time...
Optimizing Image Enhancement: Feature Engineering for Improved Classification in AI-Assisted Artificial Retinas.
Sensors (Basel, Switzerland)
Apr 23, 2024
Artificial retinas have revolutionized the lives of many blind people by enabling their ability to perceive vision via an implanted chip. Despite significant advancements, there are some limitations that cannot be ignored. Presenting all objects capt...
Deep learning-based arterial subtraction images improve the detection of LR-TR algorithm for viable HCC on extracellular agents-enhanced MRI.
Abdominal radiology (New York)
Apr 20, 2024
PURPOSE: To determine the role of deep learning-based arterial subtraction images in viability assessment on extracellular agents-enhanced MRI using LR-TR algorithm.
Angiography, Digital Subtraction
Subtraction Technique
Magnetic Resonance Imaging
Image Interpretation, Computer-Assisted
Image Enhancement
Adult
Retrospective Studies
Sensitivity and Specificity
Female
Deep Learning
Male
Aged
Liver Neoplasms
Middle Aged
Humans
Aged, 80 and over
Carcinoma, Hepatocellular
Algorithms
Contrast Media
A Swin transformer encoder-based StyleGAN for unbalanced endoscopic image enhancement.
Computers in biology and medicine
Apr 16, 2024
With the rapid development of artificial intelligence, automated endoscopy-assisted diagnostic systems have become an effective tool for reducing the diagnostic costs and shortening the treatment cycle of patients. Typically, the performance of these...
Deep learning-based compressed SENSE improved diffusion-weighted image quality and liver cancer detection: A prospective study.
Magnetic resonance imaging
Apr 9, 2024
PURPOSE: To assess whether diffusion-weighted imaging (DWI) with Compressed SENSE (CS) and deep learning (DL-CS-DWI) can improve image quality and lesion detection in patients at risk for hepatocellular carcinoma (HCC).
Deep learning-based image reconstruction for the multi-arterial phase images: improvement of the image quality to assess the small hypervascular hepatic tumor on gadoxetic acid-enhanced liver MRI.
Abdominal radiology (New York)
Mar 21, 2024
PURPOSE: To evaluated the impact of a deep learning (DL)-based image reconstruction on multi-arterial-phase magnetic resonance imaging (MA-MRI) for small hypervascular hepatic masses in patients who underwent gadoxetic acid-enhanced liver MRI.
Unpaired deep learning for pharmacokinetic parameter estimation from dynamic contrast-enhanced MRI without AIF measurements.
NeuroImage
Mar 20, 2024
DCE-MRI provides information about vascular permeability and tissue perfusion through the acquisition of pharmacokinetic parameters. However, traditional methods for estimating these pharmacokinetic parameters involve fitting tracer kinetic models, w...
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