PURPOSE: To enable a fast and automatic deep learning-based QSM reconstruction of tissues with diverse chemical shifts, relevant to most regions outside the brain.
BACKGROUND: Public community engagement is crucial for mosquito surveillance programs. To support community participation, one of the approaches is assisting the public in recognizing the mosquitoes that carry pathogens. Therefore, this study aims to...
Since segmentation labeling is usually time-consuming and annotating medical images requires professional expertise, it is laborious to obtain a large-scale, high-quality annotated segmentation dataset. We propose a novel weakly- and semi-supervised ...
Retinal vessel segmentation is extremely important for risk prediction and treatment of many major diseases. Therefore, accurate segmentation of blood vessel features from retinal images can help assist physicians in diagnosis and treatment. Convolut...
Computational and mathematical methods in medicine
Jun 17, 2022
OBJECTIVE: Its goal was to see how convolutional neural network- (CNN-) based superresolution (SR) technology magnetic resonance imaging- (MRI-) assisted transition care (TC) affected the prognosis of children with severe viral encephalitis (SVE) and...
AIM: Although MRI has a substantial role in directing treatment decisions for locally advanced rectal cancer, precise interpretation of the findings is not necessarily available at every institution. In this study, we aimed to develop artificial inte...
The characteristics of bone fragments are the main influencing factors for the choice of treatment in intertrochanteric fractures. This study aimed to develop a deep learning algorithm for recognizing and segmenting individual fragments in CT images ...
Neural networks : the official journal of the International Neural Network Society
Jun 16, 2022
We study the expressive power of deep ReLU neural networks for approximating functions in dilated shift-invariant spaces, which are widely used in signal processing, image processing, communications and so on. Approximation error bounds are estimated...
In recent years, progressive application of convolutional neural networks in image processing has successfully filtered into medical diagnosis. As a prerequisite for images detection and classification, object segmentation in medical images has attra...
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