Precise Path Planning for Robot-assisted Craniotomy: A CT-driven Virtual Center Method [0.03%]
一种CT驱动的虚拟中心法的机器人辅助开颅手术精确路径规划方法
Li Zhichao,Wenqing Ren,Hao Ren et al.
Li Zhichao et al.
Craniotomy is a critical prerequisite for numerous neuro-surgeries, including intracranial tumor resection and cerebral hemorrhage decompression. However, conventional manual craniotomy methods are often time-consuming, labor-intensive, and...
Optimized Hybrid RNN-GRU Model for Predictive Diagnosis of Cardiovascular Disease [0.03%]
一种优化的RNN-GRU混合模型的心血管疾病预测诊断方法
Gaurav Kumar,Neeraj Varshney
Gaurav Kumar
Cardiovascular disease (CVD) continues to be the leading cause of death for individuals all over the globe, and India bears a disproportionate share of the burden associated with this condition. A hybrid deep learning model that combines Re...
Design and Simulation of High-Performance PET Scanners Based on Monolithic-like BGO crystals Using GATE Monte Carlo Toolkit [0.03%]
基于GATE蒙特卡洛工具包的单片式BGO晶体高性能PET扫描仪的设计与仿真
Mohammad Babaei Ghane,Alireza Sadremomtaz,Maryam Saed
Mohammad Babaei Ghane
PET is a highly sensitive imaging modality for visualizing metabolic processes. 
Objective: This study evaluates PET scanner designs using monolithic-like BGO detector crystals, aimed at enhancing sensitivity while having minimal impact...
Flexible and transparent microelectrode arrays for simultaneous fMRI and single-spike recording in subcortical networks [0.03%]
用于皮层下神经网络的同步fMRI和单脉冲记录的柔性透明微电极阵列
Scott Greenhorn,Veronique Coizet,Océane Terral et al.
Scott Greenhorn et al.
Current techniques of neuroimaging, including electrical devices, are either of low spatiotemporal resolution or invasive, impeding multiscale monitoring of brain activity at both single-cell and network levels. Overcoming this issue is of ...
Quantitative Photo-Acoustic Imaging based on data normalisation : application to the reconstruction of the opto-mechanical properties of the intervertebral disc [0.03%]
基于数据规范化的定量光声成像在椎间盘光学力学特性逆问题中的应用研究
Antoine Capart,Roman Allais,Julien Wojak et al.
Antoine Capart et al.
The inverse problem in quantitative photoacoustic imaging (QPAI), particularly in optical inversion, presents significant challenges for accurate image reconstruction due to the nonlinearity of photoacoustic signal. In this study, we introd...
Identifying EEG-Based Neurobehavioral Risk Markers of Gaming Addiction Using Machine Learning and Iowa Gambling Task [0.03%]
基于EEG的行为危险标记物识别网络游戏成瘾者使用的机器学习和爱荷华赌博任务(IoGT)
Denis Kornev,Roozbeh Sadeghian,Amir Gandjbakhche et al.
Denis Kornev et al.
Internet Gaming Disorder (IGD), Gaming Disorder (GD), and Internet Addiction represent behavioral patterns with significant psychological and neurological consequences. Affected individuals often disengage from routine activities and exhibi...
Neurofeedback & P300 Toolbox for Neurorehabilitation: Measurement and Analysis of Brain Activity, Network and Cognitive Decline-related P300 [0.03%]
神经反馈及P300工具箱在神经康复中的应用：脑活动、网络和与认知衰退相关的P300的测量与分析
Eunggyu Lee,Youjin Kang,Hyunjin Kim et al.
Eunggyu Lee et al.
Neurofeedback is a training technique to modulate neural functions by training self-regulation of brain activity in real-time. This technique has been applied in neurorehabilitation in patients with neurological and cognitive disorders. In ...
Undulations and bending in peripheral nerves benefit coil positions projecting transverse fields [0.03%]
周围神经的波动和弯曲有利于横向磁场的线圈位置投影
Jonathan Rapp,Bojan Sandurkov,Alexandra Lindenthal et al.
Jonathan Rapp et al.
For peripheral magnetic stimulation it is widely accepted that the field components parallel to the nerve are responsible for stimulation. However, experimental findings have often suggested that transverse field components contribute as we...
DCDSN: dual-color domain siamese network for multi-classification of pathological artifacts [0.03%]
用于病理伪影多分类的双色域暹罗网络(DCDSN)
Wei-Long Ding,Jin-Long Liu,Wei Zhu et al.
Wei-Long Ding et al.
Pathological images are prone to artifacts during scanning and preparation, which can compromise diagnostic accuracy. Therefore, robust artifact detection is essential for improving image quality and ensuring reliable pathological assessmen...
A Novel sEMG-Based Hand Gesture Prediction Method Using a New Motion Detection Algorithm and an LCNN Model [0.03%]
一种基于新运动检测算法和LCNN模型的sEMG手势预测方法
Jiapeng Wang,Zhiheng Sheng
Jiapeng Wang
This paper proposes a novel gesture prediction method for accurately predicting hand gesture types from raw sEMG signals in real time. First, we utilize a linear combination of the mean and standard deviation of sEMG signals within a slidin...