[HTML][HTML] A review of deep learning-based detection methods for COVID-19
COVID-19 is a fast-spreading pandemic, and early detection is crucial for stopping the
spread of infection. Lung images are used in the detection of coronavirus infection. Chest X …
spread of infection. Lung images are used in the detection of coronavirus infection. Chest X …
Multi-scale attention generative adversarial network for medical image enhancement
High quality medical images are not only an important basis for doctors to carry out clinical
diagnosis and treatment, but also conducive to downstream tasks such as image analysis …
diagnosis and treatment, but also conducive to downstream tasks such as image analysis …
A novel method based on Wiener filter for denoising Poisson noise from medical X-Ray images
V Göreke - Biomedical Signal Processing and Control, 2023 - Elsevier
Abstract Background and Objective The Poisson noise is added to the image during the
acquisition of medical X-Ray images. The distorted image due to this noise makes it difficult …
acquisition of medical X-Ray images. The distorted image due to this noise makes it difficult …
Protein acetylation sites with complex-valued polynomial model
W Bao, B Yang - Frontiers of Computer Science, 2024 - Springer
Protein acetylation refers to a process of adding acetyl groups (CH3CO-) to lysine residues
on protein chains. As one of the most commonly used protein post-translational …
on protein chains. As one of the most commonly used protein post-translational …
Classification of breast cancer histology images using MSMV-PFENet
L Liu, W Feng, C Chen, M Liu, Y Qu, J Yang - Scientific Reports, 2022 - nature.com
Deep learning has been used extensively in histopathological image classification, but
people in this field are still exploring new neural network architectures for more effective and …
people in this field are still exploring new neural network architectures for more effective and …
An application of deep dual convolutional neural network for enhanced medical image denoising
This work investigates the medical image denoising (MID) application of the dual denoising
network (DudeNet) model for chest X-ray (CXR). The DudeNet model comprises four …
network (DudeNet) model for chest X-ray (CXR). The DudeNet model comprises four …
An adaptive watershed segmentation based medical image denoising using deep convolutional neural networks
A Annavarapu, S Borra - Biomedical Signal Processing and Control, 2024 - Elsevier
Until today, researchers have introduced a range of methodologies to decrease the noise
effect on medical images. In the proposed approach, an adapted deep convolutional neural …
effect on medical images. In the proposed approach, an adapted deep convolutional neural …
Depth restoration in under-display time-of-flight imaging
Under-display imaging has recently received considerable attention in both academia and
industry. As a variation of this technique, under-display ToF (UD-ToF) cameras enable depth …
industry. As a variation of this technique, under-display ToF (UD-ToF) cameras enable depth …
Adaptive stepsize estimation based accelerated gradient descent algorithm for fully complex-valued neural networks
W Zhao, H Huang - Expert Systems with Applications, 2024 - Elsevier
Nesterov accelerated gradient (NAG) method is an efficient first-order algorithm for
optimization problems. To ensure the convergence, it usually takes a relatively conservative …
optimization problems. To ensure the convergence, it usually takes a relatively conservative …
Quantifying innervation facilitated by deep learning in wound healing
AS Mehta, S Teymoori, C Recendez, D Fregoso… - Scientific Reports, 2023 - nature.com
The peripheral nerves (PNs) innervate the dermis and epidermis, and are suggested to play
an important role in wound healing. Several methods to quantify skin innervation during …
an important role in wound healing. Several methods to quantify skin innervation during …