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Segmentation of anterior cruciate ligament images by fusing inflated convolution and residual hybrid attention

Shengwu Yixue Gongchengxue Zazhi/Journal of Biomedical engineering 2025年第2期42卷 246-254页

作者： Shang, Peng Wang, Yuling College of Information Engineering East China University of Technology Nanchang330000 China Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and system East China University of Technology Nanchang330000 China

Aiming at the problems of low accuracy and large difference of segmentation boundary distance in anterior cruciate ligament (ACL) image segmentation of knee joint, this paper proposes an ACL image segmentation model by fusing dilated convolution and residual hybrid attention U-shaped network (DRH-UNet). The proposed model builds upon the U-shaped network (U-Net) by incorporating dilated convolutions to expand the receptive field, enabling a better understanding of the contextual relationships within the image. Additionally, a residual hybrid attention block is designed in the skip connections to enhance the expression of critical features in key regions and reduce the semantic gap, thereby improving the representation capability for the ACL area. This study constructs an enhanced annotated ACL dataset based on the publicly available Magnetic Resonance Imaging Network (MRNet) dataset. The proposed method is validated on this dataset, and the experimental results demonstrate that the DRH-UNet model achieves a Dice similarity coefficient (DSC) of (88.01±1.57)% and a Hausdorff distance (HD) of 5.16±0.85, outperforming other ACL segmentation methods. The proposed approach further enhances the segmentation accuracy of ACL, providing valuable assistance for subsequent clinical diagnosis by physicians. © 2025 West China Hospital, Sichuan Institute of Biomedical engineering. All rights reserved.

关键词： Knee prostheses

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Area Coverage Reliability Evaluation for Collaborative Intelligence and Meta-Computing of Decentralized Industrial Internet of Things

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IEEE Internet of Things Journal 2025年第10期12卷 13734-13745页

作者： Zhu, Chenlu Fan, Xiaoxuan Deng, Xianjun Liu, Shenghao Yin, Duan Gao, Hanjun Yang, Laurence T. Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan China China Mobile Communications Group Terminal Co Beijing China CNNC Wuhan Nuclear Power Operation Technology Co Wuhan China

Industrial Internet of Things (IIoT) is evolving towards decentralization and autonomous operation. Nodes in decentralized IIoT collaboratively sense data and communicate to participate in meta-computing and provide diverse intelligent services. Area coverage reliability evaluates the information collaborative intelligence sensing and communication capabilities of nodes in decentralized IIoT for a target area. It serves as a crucial performance evaluation metric for the meta-computing and intelligent services of decentralized IIoT. Existing area coverage reliability evaluation algorithms do not consider the dynamic node states in decentralized IIoT, and overlook the capability of nodes to collaborate in meta-computing. To address these issues, this paper proposes a novel Confident Information Coverage (CIC)-based area coverage reliability metric (CACREL), which comprehensively considers node multistate, node collaboration, network coverage rate, and network connectivity. To effectively evaluate CACREL, a CIC-based coverage reliability evaluation algorithm (CACR) is proposed. Specifically, CACR transforms complex networks into grid networks and utilizes a Coverage Table (CT) to describe different coverage states of each grid, which reduces the complexity of the area coverage reliability evaluation. Additionally, CACR employs a reliable path algorithm to converge the CT of each grid to the sink node based on grid connectivity. Simulation results demonstrate that the proposed CACR can accurately evaluate the area coverage reliability of decentralized IIoT and enhance its service performance. © 2014 IEEE.

关键词： Decentralized finance

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An efficient retrieval of relational database information based on knowledge graph

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International Journal of Information and Communication Technology 2023年第3期23卷 201-214页

作者： Zhu, Hongqin Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System East China University of Technology Jiangxi Nanchang330013 China Department of Information Engineering East China University of Technology 418 Guanglan Avenue Jiangxi Province Nanchang330013 China

In order to optimise the effect of database information retrieval and overcome the problem of high index cost of traditional retrieval methods, an efficient retrieval design method of relational database based on knowledge graph is designed in this paper. Firstly, the distribution model of database information retrieval nodes is constructed to analyse the data structure, and the semantic characteristics of stored data of retrieval nodes are fused. Then the knowledge graph model analysis method is used to retrieve the database node attribute clustering and adaptive scheduling to realise the design of efficient information retrieval model for the database. The experimental results show that the index distance cost of this method is always below 5 × 1,010 byte, and the index distance cost is always below 40 s, which has certain application value. © 2023 Inderscience Enterprises Ltd.

关键词： Information retrieval

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A method for detecting flower collision based on spherical projection 1

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13th Conference on Image and Graphics Technologies and Applications, IGTA 2018

作者： Cao, Tingrong Lu, Ling Wang, Wenli Li, Lihua Wang, Lei Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data Technology East China University of Technology Nanchang China Jiangxi Engineering Research Center of Nuclear Geoscience Data Science and System East China University of Technology Nanchang China

ISBN: (数字)9789811317026

ISBN: (纸本)9789811317019

In this paper, a method for detecting and mapping the petals of plant petals is presented. Firstly, the parametric equations are used to represent the initial state of the petals surface. The three - dimensional Cartesian coordinates of each point in the petals are projected onto the spherical coordinates respectively, The discrete values of the projection of the petals are converted to the two-dimensional coordinate plane. Secondly, multiple buffers are used to record the result of each petals projection and the distance of the petals from the origin of the spherical coordinates. According to the value of each buffer, it is determined whether the current petal collides with others, the collides result can be determined the range of collision. Finally, the current petals are deformed or moved to avoid collided with others. Through the collision test between the petals in the process of flower generation, it shows that the detection effect is good. © Springer Nature Singapore Pte Ltd., 2018.

关键词： Spheres

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Signal modeling and impulse response shaping for semiconductor detectors

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nuclear science and Techniques 2022年第4期33卷 72-82页

作者： Xue-Yuan Wang Jian-Bin Zhou Ming Wang Huai-Ping Wang Xu Hong Yi Liu Ping Huang College of Nuclear Technology and Automation Engineering Chengdu University of TechnologyErxian BridgeNo.1 East 3 RoadChenghua DistrictChengdu 610059China Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System East China University of TechnologyNanchang 330013China China Testing Technology Co. LtdChengdu 610021China

The output-signal models and impulse response shaping(IRS)functions of semiconductor detectors are important for establishing high-precision measurement *** this paper,an output-signal model for semiconductor detector systems is *** to the proposed model,a multistage cascade deconvolution IRS algorithm was developed using the C-R inverse system,R-C inverse system,and differentiator *** silicon drift detector signals acquired from the analog-to-digital converter were *** experimental results indicated that the shaped pulses obtained using the proposed model had no undershoot,and the average peak base width of the output shaped pulses was reduced by 36%compared with that for a simple model proposed in a previous work[1].Offline processing results indicated that compared with the traditional IRS algorithm,the average peak base width of the output shaped pulses obtained using the proposed algorithm was reduced by 11%,and the total elapsed time required for pulse shaping was reduced by 26%.The proposed algorithm avoids recursive *** the sampling frequency of the digital system reaches 100 MHz,the proposed algorithm can be simplified to integer *** proposed IRS algorithm can be applied to high-resolution energy spectrum analysis,highcounting rate energy spectrum correction,and coincidence and anti-coincidence measurements.

关键词： Output-signal model Impulse response shaping C-R inverse system R-C inverse system Integer arithmetic

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Design of vehicle management reader based on STM32

Design of vehicle management reader based on STM32

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2020 International Conference on Applied Physics and Computing, ICAPC 2020

作者： Ding, Chenglong Liu, Zhifeng Xu, Yuefeng Shu, Zhihao Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System East China University of Technology Nanchang Jiangxi330013 China School of Information Engineering East China University of Technology China

This paper mainly studies the parking lot counting system, which is a modern and new system integrating detection and conversion technology, computer technology, information processing, digital technology and other technologies. This work uses STM32F103 single-chip microcomputer as the MCU processor, and uses 2 infrared modules to detect vehicle access. Through the single-chip microcomputer, information is collected to detect vehicle access. LCD12864 is used to display vehicle parking information for drivers to watch. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Microcomputers

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Optimization of EPMA Image Reconstruction Based on Generalized Orthogonal Matching Pursuit Algorithm 2020

Optimization of EPMA Image Reconstruction Based on Generaliz...

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2020 International Conference on Computing, Networks and Internet of Things, CNIOT 2020

作者： Jin, Anan Li, Xiang School of Information Engineering East China University of Technology Nanchang China Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System East China University of Technology Nanchang Jiangxi Province China

ISBN: (纸本)9781450377713

In the realm of Compressed Sensing (CS), Orthogonal Matching Pursuit (OMP) algorithm is widely acknowledged. The generalized Orthogonal Matching Pursuit (gOMP) algorithm is an improved OMP approach. However, it demonstrates low reconstruction accuracy for electron probe images based on our experiments. This paper enhances gOMP by adjusting the algorithm parameters according to the characteristics of electron probe images. An optimal sparsity (K) and the atom selection numbers (S) matching with best parameters for gOMP is selected through experiments. Besides that, Fourier measurement matrix has been identified after evaluation of various measurement matrices. The improved algorithm, Fourier's generalized Orthogonal Matching Pursuit (FgOMP), is constructed based on these findings. The simulation results show that the proposed algorithm can achieve Super Resolution Recovery requirements and provide a significant higher reconstruction quality for electronic probe images than the original gOMP algorithm and other relevant algorithms. © 2020 ACM.

关键词： Compressed sensing

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The application of decision tree in the prediction of winning team

The application of decision tree in the prediction of winnin...

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2018 International Conference on Virtual Reality and Intelligent systems, ICVRIS 2018

作者： Tang, Xiaohu Liu, Zhifeng Li, Taizhao Wu, Wenbin Wei, Zhenhua Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data Technology East China University of Technology Nanchang Jiangxi330013 China Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System East China University of Technology Nanchang Jiangxi330013 China Information Engineering College East China University of Technology Nanchang Jiangxi330013 China

ISBN: (纸本)9781538680315

Decision tree algorithm is mainly used for analyzing data and *** algorithm is easy to understand and implement, and it is easy to evaluate the model through static *** this paper, the decision tree algorithm is applied to predict the result of Chinese Football Association Super League(CFASL). In this paper, the data of CFASL 2015, 2016 and 2017 seasons are collected. And 'the result of each team's last match', 'compare of teams' ranking in last season', 'the result of last time the two teams played',etc. are selected as features to predict the winner of a CFASL match. The experiments found that 'two teams' performance in their recent matches', 'whether team A has defeated team B as an away team' and 'whether team B has defeated team A as an away team' played a key role in improving the accuracy of predicting. © 2018 IEEE.

关键词： Forecasting

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Self-organizing Competitive Neural Network Based Adaptive Sparse Representation for Magnetotelluric data Denoising 10

Self-organizing Competitive Neural Network Based Adaptive Sp...

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10th International Conference on Environmental and engineering Geophysics, ICEEG 2023

作者： Liu, Xiaoqiong Li, Guang Li, Jin Zhou, Xiaohui Gu, Xianjie Zhou, Cong Gong, Meng Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System East China University of Technology Nanchang330013 China College of Information Science and Engineering Hunan Normal University Changsha410081 China

The existing sparse decomposition denoising methods for magnetotelluric (MT) data need to set the iterative stop condition manually, which not only has a large workload and high difficulty, but also easily causes subjective bias. To this end, we propose a new adaptive sparse representation method for MT data denoising. First, the data to be processed is divided into high-quality segments and noisy segments by machine learning algorithm. Then, the characteristic parameters of high-quality segments are calculated, and the boundary value of the characteristic parameters is taken as the threshold. The threshold has two functions, one is as a criterion for signal-to-noise identification, and the other is as an iterative stop condition for subsequent sparse decomposition. Finally, the optimized orthogonal matching pursuit algorithm is used to separate the signal and noise of the noisy segments, and the denoised segments and high-quality segments are combined to obtain the complete denoised MT data. The field data processing results show that this method is a fully automatic and intelligent MT data denoising method. It greatly improves the signal-to-noise ratio and the apparent resistivity-phase curves. © Published under licence by IOP Publishing Ltd.

关键词： Signal to noise ratio

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Earthquake big data processing and visualization based on PyEcharts 3

Earthquake big data processing and visualization based on Py...

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3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2023

作者： Wu, Jiandong Wang, Qiang Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System East China University of Technology Nanchang China Software School of East China University of Technology Nanchang China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

This paper mainly uses the Python language and the pyecharts library to mine the earthquake data that occurred around the world in 2020, and finally displays it with pie charts, bar charts and other graphics. It lays a foundation for better use and processing of earthquake big data in the future, and also demonstrates the application of big data in other industries. © 2023 SPIE.

关键词： Visualization

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