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| 1 | 基于拉普拉斯算子与统计形状模型的股骨三维重建方法显示文摘通过二维图像进行重建的三维模型,是目前术前规划、人工关节定制的普遍需求。本文提出一种统计形状模型与拉普拉斯曲面变形相结合的方法,应用于股骨图像的三维重建,以优化传统统计建模重建过程中特征不足和信息损失造成的精度问题。该方法将基于统计形状模型的重建结果用能够代表形状特征的拉普拉斯算子表示,在拉普拉斯坐标系下进行曲面结点坐标变换,建立骨骼新特征,使重建模型与二维图像充分拟合。最后选取50例股骨模型验证本方法的有效性。结果表明,引入拉普拉斯曲面变形后的方法较传统统计形状模型的精度提升了16.8%~25.9%。该方法能够以更高精度完成骨三维重建,为术前个性化假体设计及其精准定位与快速生物力学分析等研究提供模型基础。 | 张祖佩 张小刚 张亚丽 靳忠民 | 2023 | 生物医学工程学杂志2023，40，6： | 0 |
| 2 | Automated Silicon-Substrate Ultra-Microtome for Automating the Collection of Brain Sections in Array Tomography显示文摘Understanding the structure and working principle of brain neural networks requires three-dimensional reconstruction of brain tissue samples using array tomography method.In order to improve the reconstruction performance,the sequence of brain sections should be collected with silicon wafers for subsequent electron microscopic imaging.However,the current collection of brain sections based on silicon substrate involve mainly manual collection,which requires the involvement of automation techniques to increase collection efficiency.This paper presents the design of an automatic collection device for brain sections.First,a novel mechanism based on circular silicon substrates is proposed for collection of brain sections;second,an automatic collection system based on microscopic object detection and feedback control strategy is proposed.Experimental results verify the function of the proposed collection device.Three objects(brain section,left baffle,right baffle)can be detected from microscopic images by the proposed detection method.Collection efficiency can be further improved with position feedback of brain sections well.It has been experimentally verified that the proposed device can well fulfill the task of automatic collection of brain sections.With the help of the proposed automatic collection device,human operators can be partially liberated from the tedious manual collection process and collection efficiency can be improved. | Long Cheng Weizhou Liu Chao Zhou Yongxiang Zou Zeng-Guang Hou | 2021 | IEEE/CAA Journal of Automatica Sinica2021，8，2： | 0 |
| 3 | Energy consumption optimization for edge computing-supported cellular networks based on optimal transport theory显示文摘With advancements in mobile communication technologies,there have been multiple user device(UD)connections to cellular networks.Because of changes in the spatial distribution of UDs and application requirements,the traditional offloading mechanism based on the nearest distance will result in heavy loads for some base stations(BSs).Because there is a high-order relationship between the energy consumption of the BS processing tasks and the number of computing tasks,the traditional offloading mechanism will result in high energy consumption,and UD’s offloading decision must be dynamically adjusted.The offloading decision of UDs is optimized based on detailed information about various parameters associated with a network from the standpoint of distribution.This information includes details regarding the spatial distribution of UDs,application requirements,and the offloading period of computing tasks.Based on optimal transport theory,an energy consumption optimization algorithm is suggested to lower the total amount of energy consumed by the offloading process of UDs’computing tasks by reasonably planning the offloading BSs of the UDs in the networks.The simulation results show that the proposed offloading mechanism based on energy consumption optimization reduces the total energy consumption of the offloading process by 28.09%when compared to the traditional offloading mechanism,and the traffic managed by each BS is balanced. | Xiangyu LV Xiaohu GE Yi ZHONG Qiang LI Yong XIAO | 2024 | Science China(Information Sciences)2024，67，2： | 0 |
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