The study aimed to develop and validate a convolutional neural network (CNN)-based deep learning method for automatic diagnosis and graduation of skin frostbite. A dataset of 71 annotated images was used for the training, the validation, and the test...
Screening and diagnosis of diabetic retinopathy disease is a well known problem in the biomedical domain. The use of medical imagery from a patient's eye for detecting the damage caused to blood vessels is a part of the computer-aided diagnosis that ...
AJNR. American journal of neuroradiology
Jul 28, 2022
BACKGROUND AND PURPOSE: Accurate quantification of WM lesion load is essential for the care of patients with multiple sclerosis. We tested whether the combination of accelerated 3D-FLAIR and denoising using deep learning-based reconstruction could pr...
The objective of the current study was to investigate the performance of various deep learning (DL) architectures for MyoMapNet, a DL model for T estimation using accelerated cardiac T mapping from four T -weighted images collected after a single inv...
Computational intelligence and neuroscience
Jun 21, 2022
Geometric ability includes elements of identification, conceptualization, combination, drawing, and reasoning, and graphic perception is an important part of it. Kindergarten science education includes geometry instruction. Children are guided to per...
The purpose of this study is to evaluate whether thin-slice high-resolution 2D fat-suppressed proton density-weighted image of the knee joint using denoising approach with deep learning-based reconstruction (dDLR) with MPR is more useful than 3D FS-P...
In myocardial T mapping, undesirable motion poses significant challenges because uncorrected motion can affect T estimation accuracy and cause incorrect diagnosis. In this study, we propose and evaluate a motion correction method for myocardial T map...
Research using whole slide images (WSIs) of histopathology slides has increased exponentially over recent years. Glass slides from retrospective cohorts, some with patient follow-up data are digitised for the development and validation of artificial ...
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