Journal of imaging informatics in medicine
Jul 17, 2024
Wound management requires the measurement of the wound parameters such as its shape and area. However, computerized analysis of the wound suffers the challenge of inexact segmentation of the wound images due to limited or inaccurate labels. It is a c...
Journal of imaging informatics in medicine
Jul 17, 2024
Multiple studies within the medical field have highlighted the remarkable effectiveness of using convolutional neural networks for predicting medical conditions, sometimes even surpassing that of medical professionals. Despite their great performance...
The aim of this study was to develop an optimal, simple, and lightweight deep learning convolutional neural network (CNN) model to detect the presence of mesiodens on panoramic radiographs. A total of 628 panoramic radiographs with and without mesiod...
Neural networks : the official journal of the International Neural Network Society
Jul 17, 2024
The increasing size of pre-trained language models has led to a growing interest in model compression. Pruning and distillation are the primary methods employed to compress these models. Existing pruning and distillation methods are effective in main...
Neural networks : the official journal of the International Neural Network Society
Jul 17, 2024
Multi-modal representation learning has received significant attention across diverse research domains due to its ability to model a scenario comprehensively. Learning the cross-modal interactions is essential to combining multi-modal data into a joi...
Social media networks become an active communication medium for connecting people and delivering new messages. Social media can perform as the primary channel, where the globalized events or instances can be explored. Earlier models are facing the pi...
Neural networks : the official journal of the International Neural Network Society
Jul 17, 2024
Current state-of-the-art medical image segmentation techniques predominantly employ the encoder-decoder architecture. Despite its widespread use, this U-shaped framework exhibits limitations in effectively capturing multi-scale features through simpl...
To evaluate the feasibility of acquiring vertebral height from chest low-dose computed tomography (LDCT) images using an artificial intelligence (AI) system based on 3D U-Net vertebral segmentation technology and the correlation and features of verte...
International journal of neural systems
Jul 17, 2024
Recently, Graph Neural Networks (GNNs) have gained widespread application in automatic brain network classification tasks, owing to their ability to directly capture crucial information in non-Euclidean structures. However, two primary challenges per...
BACKGROUND: X-ray radiography is a widely used imaging technique worldwide, and its image quality directly affects diagnostic accuracy. Therefore, X-ray image quality control (QC) is essential. However, subjectively assessing image quality is ineffic...
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