[Coronary artery segmentation based on Transformer and convolutional neural networks dual parallel branch encoder neural network] [0.03%]
基于Transformer和卷积神经网络双并行分支编码器神经网络的冠状动脉分割研究
Dan Pan,Genqiang Luo,An Zeng
Dan Pan
Manual segmentation of coronary arteries in computed tomography angiography (CTA) images is inefficient, and existing deep learning segmentation models often exhibit low accuracy on coronary artery images. Inspired by the Transformer archit...
[Image reconstruction for cerebral hemorrhage based on improved densely-connected fully convolutional neural network] [0.03%]
基于改进稠密连接全卷积神经网络的脑出血图像重建
Yanyan Shi,Luanjun Wang,Yating Li et al.
Yanyan Shi et al.
Cerebral hemorrhage is a serious cerebrovascular disease with high morbidity and high mortality, for which timely diagnosis and treatment are crucial. Electrical impedance tomography (EIT) is a functional imaging technique which is able to ...
[The dual-stream feature pyramid network based on Mamba and convolution for brain magnetic resonance image registration] [0.03%]
基于Mamba和卷积的双流特征金字塔网络脑部磁共振图像配准方法
Linjie Fu,Yaoyao Zhu,Yu Yao
Linjie Fu
Deformable image registration plays a crucial role in medical image analysis. Despite various advanced registration models having been proposed, achieving accurate and efficient deformable registration remains challenging. Leveraging the re...
[A novel approach for assessing quality of electrocardiogram signal by integrating multi-scale temporal features] [0.03%]
通过整合多尺度时间特征评估心电图信号质量的新方法
Cheng Chen,Aihua Zhang,Yurun Ma et al.
Cheng Chen et al.
During long-term electrocardiogram (ECG) monitoring, various types of noise inevitably become mixed with the signal, potentially hindering doctors' ability to accurately assess and interpret patient data. Therefore, evaluating the quality o...
[Study on the regulatory effect of low intensity retinal ultrasound stimulation on the neural activity of visual cortex] [0.03%]
低强度视网膜超声刺激对视觉皮层神经元活动影响的研究
Qianqian Wang,Yi Yuan,Jiaqing Yan
Qianqian Wang
Low-intensity ultrasound stimulation of the retina has the ability to modulate neural activity in the primary visual cortex (V1), however, it is currently unclear how different intensities and durations of ultrasonic stimulation of the reti...
[Gesture accuracy recognition based on grayscale image of surface electromyogram signal and multi-view convolutional neural network] [0.03%]
基于表面肌电图灰度图像和多视角卷积神经网络的手势精度识别
Qingzheng Chen,Qing Tao,Xiaodong Zhang et al.
Qingzheng Chen et al.
This study aims to address the limitations in gesture recognition caused by the susceptibility of temporal and frequency domain feature extraction from surface electromyography signals, as well as the low recognition rates of conventional c...
[Three-dimensional convolutional neural network based on spatial-spectral feature pictures learning for decoding motor imagery electroencephalography signal] [0.03%]
基于空间光谱特征图像学习的解码运动想象脑电图信号的三维卷积神经网络
Xuejian Wu,Yaqi Chu,Xingang Zhao et al.
Xuejian Wu et al.
The brain-computer interface (BCI) based on motor imagery electroencephalography (EEG) shows great potential in neurorehabilitation due to its non-invasive nature and ease of use. However, motor imagery EEG signals have low signal-to-noise ...
[Design and research of a pneumatic soft intestine robot imitating the inchworm] [0.03%]
模仿尺蠖的气动软肠道机器人设计与研究
Yongsheng He,Zhijun Sun,Jie Yuan et al.
Yongsheng He et al.
In order to seek a patient friendly and low-cost intestinal examination method, a structurally simple pneumatic soft intestinal robot inspired by inchworms is designed and manufactured. The intestinal robot was consisted of two radially exp...
[Sampling intervals dependent feature extraction for state transfer networks of epileptic signals] [0.03%]
基于状态转移网络的癫痫信号采样间隔相关特征提取
Lei Zhang,Shuang Yan,Changgui Gu
Lei Zhang
Epileptic seizures and the interictal epileptiform discharges both have similar waveforms. And a method to effectively extract features that can be used to distinguish seizures is of crucial importance both in theory and clinical practice. ...
[Fusion of electroencephalography multi-domain features and functional connectivity for early dementia recognition] [0.03%]
[脑电多域特征及功能连接融合的早期痴呆识别]
Wenwen Chang,Lei Zheng,Guanghui Yan et al.
Wenwen Chang et al.
Dementia is a neurodegenerative disease closely related to brain network dysfunction. In this study, we assessed the interdependence between brain regions in patients with early-stage dementia based on phase-lock values, and constructed a f...