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BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2023年第6期20卷 824-835页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

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The research of extraordinary transmission through a new type of double-layer metal film material 9

The research of extraordinary transmission through a new typ...

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9th International Conference on Microwave and Millimeter Wave Technology, ICMMT 2016

作者： Yang, Hou Minquan, Li Yadong, Wei Xuyun, Long Yuan, Zhu Key Laboratory of Computational Intelligence and Signal Processing of Ministry of Education Anhui University Hefei230039 China

ISBN: (纸本)9781467389815

Due to the shielding effects of metal to the electromagnetic wave, when the thickness of the metal film is greater than the wavelength of the incident wave, the electromagnetic wave can't get through the metal film. This paper designed a new type of double-layer metal subwavelength circle array structure, by etching subwavelength holes on each layer of metal film and adding a metal cylinder at the center of each round hole. When electromagnetic waves irradiate on the structure, some specific frequencies electromagnetic waves can get through the metal film and generate the extraordinary transmission phenomenon. We studied the transmission characteristics of this array by finite element method, comparing and analyzing the influence on transmission characteristics affected by the thickness of the metal film, the period of array, the distance of holes center and metal cylinder radius. We give a reasonable explanation for the results and the extraordinary transmission. These results may provide certain significant reference to electromagnetic waves regulation and the extraordinary transmission phenomenon. © 2016 IEEE.

关键词： Electromagnetic waves

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An Early Stage Researcher's Primer on Systems Medicine Terminology

Network and Systems Medicine

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Network and Systems Medicine 2021年第1期4卷 2-50页

作者： Zanin, Massimiliano Aitya, Nadim A.A. Basilio, José Baumbach, Jan Benis, Arriel Behera, Chandan K. Bucholc, Magda Castiglione, Filippo Chouvarda, Ioanna Comte, Blandine Dao, Tien-Tuan Ding, Xuemei Pujos-Guillot, Estelle Filipovic, Nenad Finn, David P. Glass, David H. Harel, Nissim Iesmantas, Tomas Ivanoska, Ilinka Joshi, Alok Boudjeltia, Karim Zouaoui Kaoui, Badr Kaur, Daman Maguire, Liam P. McClean, Paula L. McCombe, Niamh De Miranda, João Luís Moisescu, Mihnea Alexandru Pappalardo, Francesco Polster, Annikka Prasad, Girijesh Rozman, Damjana Sacala, Ioan Sanchez-Bornot, Jose M. Schmid, Johannes A. Sharp, Trevor Solé-Casals, Jordi Spiwok, Vojtěch Spyrou, George M. Stalidzans, Egils Stres, Blaa Sustersic, Tijana Symeonidis, Ioannis Tieri, Paolo Todd, Stephen Van Steen, Kristel Veneva, Milena Wang, Da-Hui Wang, Haiying Wang, Hui Watterson, Steven Wong-Lin, Kongfatt Yang, Su Zou, Xin Schmidt, Harald H.H.W. Centro de Tecnología Biomédica Universidad Politécnica de Madrid Madrid Spain Intelligent Systems Research Centre School of Computing Engineering and Intelligent Systems Ulster University Ulster United Kingdom Center for Physiology and Pharmacology Institute of Vascular Biology and Thrombosis Research Medical University of Vienna Vienna Austria TUM School of Life Sciences Weihenstephan Technical University of Munich Freising Germany Holon Israel CNR National Research Council IAC Institute for Applied Computing Rome Italy Lab of Computing Medical Informatics and Biomedical Imaging Technologies School of Medicine Aristotle University of Thessaloniki Thessaloniki Greece Université Clermont Auvergne INRAE UNH Plateforme d'Exploration du Métabolisme MetaboHUB Clermont Clermont-Ferrand France Université de Technologie de Compiègne Compiègne France Labex MS2T Control of Technological Systems-of-Systems CNRS and Université de Technologie de Compiègne Compiègne France Faculty of Engineering University of Kragujevac Kragujevac Serbia Kragujevac Serbia Steinbeis Advanced Risk Technologies Institute Doo Kragujevac Kragujevac Serbia Pharmacology and Therapeutics School of Medicine Galway Neuroscience Centre National University of Ireland Galway Ireland School of Computing Ulster University Ulster United Kingdom Holon Israel Department of Mathematics and Natural Sciences Kaunas University of Technology Kaunas Lithuania Faculty of Computer Science and Engineering Ss. Cyril and Methodius University Skopje Macedonia Medicine Faculty Université Libre de Bruxelles CHU de Charleroi Charleroi Belgium Northern Ireland Centre for Stratified Medicine Biomedical Sciences Research Institute Ulster University Ulster United Kingdom Escola Superior de Tecnologia e Gestão Instituto Politécnico de Portalegre Portalegre Portugal Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal Faculty of Automatic Control and Computers University Politehnica of B

Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields. Methods: In this review, we collect and explain more than100 terms related to Systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references. Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic. © Massimiliano Zanin et al., 2021;Published by Mary Ann Liebert, Inc. 2021.

关键词： Semantics

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Author Correction: BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2024年第10期21卷 1959页

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A co-evolutionary particle swarm optimization with dynamic topology for solving multi-objective optimization problems

Advances in Modelling and Analysis A

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Advances in Modelling and Analysis A 2016年第1期53卷 145-159页

作者： Wu, Daqing Tang, Lixiang Li, Haiyan Ouyang, LiJun Computer Science and Technology Institute University of South China HangyangHunan China Antai College of Economics and Management Shanghai Jiao Tong University Shanghai200240 China Zigong643000 China Key Laboratory of Guangxi High Schools for Complex System and Computational Intelligence Guangxi University for Nationalities Nanning530006 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University HefeiAnhui Province230039 China Department of Business Administration Hunan University of Finance and Economics Hunan410205 China

This paper proposes a multi-objective with dynamic topology particle swarm optimization (PSO) algorithm for solving multi-objective problems, named DTPSO. One of the main drawbacks of classical multi-objective particle swarm optimization algorithm is low diversity. To overcome this disadvantage, DTPSO uses two dynamic local best particles to lead the search particles with multiple populations to deal with multiple objectives, and maintains diversity of new found non-dominated solutions via partitioned the searching space into fixed number of cells. The proposed DTPSO is validated through comparisons with other two multi-objective algorithms using established benchmarks and metrics. Simulation results demonstrated that DTPSO shows competitive, if not better, performance as compared to the other algorithms. © 2016, AMSE Press. All rights reserved.

关键词： Multiobjective optimization

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Substrate integrated waveguide filter with improved stopband performance using LTCC technology

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Progress In Electromagnetics Research C 2014年 54卷 155-162页

作者： Zhang, Ping-Juan Li, Min-Quan College of Mathematics Physics and Information Engineering Anhui Science and Technology University Chuzhou233100 China Key Laboratory of Intelligent Computation and Signal Processing Ministry of Education Anhui University Hefei230039 China

A novel multi-layer third-order substrate integrated waveguide (SIW) bandpass filter with improved lower stopband performance is proposed. TE201-mode in folded-SIW cavity is utilized to implement negative cross coupling, and the TE101-mode is taken as a non-resonating node (NRN) for implementing bypass coupling. A circular aperture etched on the middle metal layer is used to realize coupling between source and the second SIW cavity. Then, three transmission zeros located below the passband can be obtained to improve stopband attenuation. Meanwhile, better spurious suppression performance above passband is achieved. A filter sample is designed and fabricated with multi-layer low-temperature co-fired ceramic (LTCC) technology. The measured S-parameters agree well with the simulated ones, with its predicted good performance. © 2014 Electromagnetics Academy. All rights reserved.

关键词： Substrate integrated waveguides

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A novel hybrid intelligence algorithm for solving combinatorial optimization problems

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Journal of Computing Science and Engineering 2014年第4期8卷 199-206页

作者： Deng, Wu Chen, Han Li, He Software Institute Dalian Jiaotong University Dalian China The Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China The Artificial Intelligence Key Laboratory of Sichuan Province Sichuan University of Science and Engineering Zigong China Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis Guangxi University for Nationalities Nanning China

The ant colony optimization (ACO) algorithm is a new heuristic algorithm that offers good robustness and searching ability. With in-depth exploration, the ACO algorithm exhibits slow convergence speed, and yields local optimization solutions. Based on analysis of the ACO algorithm and the genetic algorithm, we propose a novel hybrid genetic ant colony optimization (NHGAO) algorithm that integrates multi-population strategy, collaborative strategy, genetic strategy, and ant colony strategy, to avoid the premature phenomenon, dynamically balance the global search ability and local search ability, and accelerate the convergence speed. We select the traveling salesman problem to demonstrate the validity and feasibility of the NHGAO algorithm for solving complex optimization problems. The simulation experiment results show that the proposed NHGAO algorithm can obtain the global optimal solution, achieve self-adaptive control parameters, and avoid the phenomena of stagnation and prematurity. © 2014. The Korean Institute of Information Scientists and Engineers.

关键词： Genetic algorithms

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Tensor-based Gaussian processes regression using a probabilistic kernel with information divergence

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International Journal of Simulation: Systems, Science and Technology 2015年第5期16卷 13.1-13.7页

作者： Tang, Lingbing Peng, Pin Zhao, Qibin Gui, Lihua Qing, Luochang Mobile E-business Collaborative Innovation Center of Hunan Province Hunan University of Commerce ChangshaHunan410205 China Key Laboratory of Hunan Province for Mobile Business Intelligence ChangshaHunan410205 China Lab.for Advanced Brain Signal Processing Brain Science Institute RIKEN 2-1 Hirosawa WakoshiSaitama Japan Graduate School of Engineering Saitama Institute of Technology Japan School of Finance and Banking Hunan University of Commerce ChangshaHunan410205 China

We present a Gaussian processes regression for tensor-valued inputs, which is based on a coherent treatment of a prior for the latent function with a covariance function defined on a tensor representation of multivariate data. Such a rigorous account of the underlying data dependencies within the model is also the basis for a new and powerful framework for structural data analysis. This is achieved under the assumption of generative models, and by introducing a family of probabilistic kernels with tensor arguments. By equipping these product kernels with the Jensen-Shannon divergence measure for tensorial data, the proposed model can be considered as both a generative and discriminative model. Further, a fully Bayesian treatment is used to estimate the hyperparameters and infer the predictive distributions. Experimental results on a real world application of decoding 3D movement trajectory based on electrocorticography (ECoG) signals recorded from a monkey brain demonstrate the effectiveness and performance advantage of the proposed framework. © 2015, UK Simulation Society. All rights reserved.

关键词： Tensors

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Pulse waveform key point recognition by wavelet transform for central aortic blood pressure estimation

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Journal of Information and computational Science 2012年第1期9卷 25-33页

作者： Zheng, Gang Huang, Qingjun Yan, Guodong Dai, Min Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin 300384 China Laboratory of Bio Signal and Intelligent Processing Tianjin University of Technology Tianjin 300384 China

Non invasion estimating of Central Aortic blood Pressure (CAP) is still a hard problem. Through tenyears clinical research plan (CAFE, Conduit Artery Functional Endpoint) on CAP, CAP is a vital sign to evaluate human's vascular condition. It is more valuable than ordinary brachial artery blood pressure. Non invasion estimating of CAP is depended on the key point recognition of radial pulse, especially the peak of tidal wave (left ventricular stopping ejection point, point e). Since someone's point e is not obvious in his/her pulse waveform, orientation of this point has becoming a difficult problem to be tackled. Through deep study on the feature of pulse waveform, an modified wavelet transform is proposed. It is used to recognize point e of pulse waveform by relative displacement between the 4th and 5th scale of a symlet (it is a kind of discrete wavelet transform). After experiments on 16 patients and 20 healthy volunteers, the results support the proposed strategy in recognizing both obvious and unobvious point e of pulse waveform. The CAP can be estimated by the point e accurately, and the results can meet the requirement of clinical diagnosis. © 2012 Binary Information Press January 2012.

关键词： Clinical research

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A novel design for the receiver of SAW reader

A novel design for the receiver of SAW reader

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2011 2nd International Conference on Mechanic Automation and Control Engineering, MACE 2011

作者： Liu, Kun Li, Min-Quan Key Laboratory of Intelligent Computation and Signal Processing of Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781424494392

DC-offset and 1/f noise are serious deficiencies of zero- IF receiver that it is limited in the application. A novel zero-IF receiver solution is presented to solve the problems about the DC-offset and 1/f noise of zero-IF. A receiver of the 915MHz SAW reader is designed, basing on the novel solution. The simulation platform of the circuit model and the communication system model are built under the environment of ADS. The parameters of each module are determined by calculating and simulating, combing ADIsimRF with ADS software in the receiver. The correctness of the receiver's model is verified by the bit error rate simulation with communication system model. The furthest distance for receiver identification is 12 m, while its bit error rate is smaller than 10-9. © 2011 IEEE.

关键词： Bit error rate

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