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CShaperApp:Segmenting and analyzing cellular morphologies of the developing Caenorhabditis elegans embryo

Quantitative Biology 2024年第3期12卷 329-334页

作者： Jianfeng Cao Lihan Hu Guoye Guan Zelin Li Zhongying Zhao Chao Tang Hong Yan Department of Electrical Engineering City University of Hong KongHong KongChina Centre for Intelligent Multidimensional Data Analysis Limited Hong KongChina College of Computer and Information Hohai UniversityNanjingChina Center for Quantitative Biology Peking UniversityBeijingChina Department of Biology Hong Kong Baptist UniversityHong KongChina State Key Laboratory of Environmental and Biological Analysis Hong Kong Baptist UniversityHong KongChina Peking-Tsinghua Center for Life Sciences Peking UniversityBeijingChina School of Physics Peking UniversityBeijingChina

Caenorhabditis elegans has been widely used as a model organism in developmental biology due to its invariant *** this study,we developed a desktop software CShaperApp to segment fluorescence-labeled images of cell membranes and analyze cellular morphologies interactively during *** *** on the previously proposed framework CShaper,CShaperApp empowers biologists to automatically and efficiently extract quantitative cellular morphological data with either an existing deep learning model or a fine-tuned one adapted to their in-house *** results show that it takes about 30 min to process a three-dimensional time-lapse(4D)dataset,which consists of 150 image stacks at a~1.5-min interval and covers *** embryogenesis from the 4-cell to 350-cell *** robustness of CShaperApp is also validated with the datasets from different ***,modularized implementation increases the flexibility in multi-task applications and promotes its flexibility for future *** cell morphology over development has emerged as a focus of interest in developmental biology,CShaperApp is anticipated to pave the way for those studies by accelerating the high-throughput generation of systems-level quantitative data *** software can be freely downloaded from the website of Github(cao13jf/CShaperApp)and is executable on Windows,macOS,and Linux operating systems.

关键词： C.elegans embryogenesis cellular morphology cellular segmentation deep learning desktop software

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Performance analysis for a degrading system with Markov model 32nd

Performance analysis for a degrading system with Markov mode...

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32nd European Safety and Reliability Conference, ESREL 2022

作者： Zhang, Aibo Wu, Zhiying Wang, Yukun Xie, Min Center for Intelligent Multidimensional Data Analysis Hong Kong Science Park Shatin Hong Kong Department of Advanced Design and Systems Engineering City University of Hong Kong Hong Kong Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science and Innovation Chinese Academy of Sciences Hong Kong School of Economics and Management Tianjin Chengjian University Tianjin300384 China

ISBN: (纸本)9789811851834

Most mechanical engineering systems experience deterioration due to several practical factors such as aging, usage etc. This results in the degradation of its performance. Although the deterioration is continuous in nature, it is not always practically possible to measure the deterioration especially in the case of subsea systems. In such cases the performance of these systems is represented by multiple finite states in their lifetimes where various levels of degradation are represented by these states. Generally, the degradation process is divided into two stages, i.e., the normal and defective stages. Thus, there are three possible states for the system: normal, defective, and failed. The Markov approach has been utilized heavily for reliability analysis of such systems. However, most of the Markov models rely on an accurately exponentially distributed transition rate, which is unrealistic in certain cases. In reality, there are some uncertainties in the transition rates thanks to the limits of prior knowledge. This paper presents a multi-phase Markov model-based performance evaluation model for a three-state system with uncertainties in transition rates. The transition rates are assumed following Beta distribution with known lower and upper bounds. The average system unavailability in a given life cycle is employed to quantify system performance. © 2022 ESREL2022 Organizers. Published by Research Publishing, Singapore.

关键词： Reliability analysis

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Randomized algorithms for computing the tensor train approximation and their applications

arXiv

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arXiv 2024年

作者： Che, Maolin Wei, Yimin Yan, Hong School of Mathematics and Statistics Guizhou University Guizhou Guiyang550025 China Center for Intelligent Multidimensional Data Analysis Hong Science Park Shatin Hong Kong School of Mathematical Sciences Key Laboratory of Mathematics for Nonlinear Sciences Fudan University Shanghai200433 China Department of Electrical Engineering Center for Intelligent Multidimensional Data Analysis City University of Hong Kong 83 Tat Chee Avenue Kowloon Hong Kong

In this paper, we focus on the fixed TT-rank and precision problems of finding an approximation of the tensor train (TT) decomposition of a tensor. Note that the TT-SVD and TT-cross are two well-known algorithms for these two problems. Firstly, by combining the random projection technique with the power scheme, we obtain two types of randomized algorithms for the fixed TT-rank problem. Secondly, by using the non-asymptotic theory of sub-random Gaussian matrices, we derive the upper bounds of the proposed randomized algorithms. Thirdly, we deduce a new deterministic strategy to estimate the desired TT-rank with a given tolerance and another adaptive randomized algorithm that finds a low TT-rank representation satisfying a given tolerance, and is beneficial when the target TT-rank is not known in advance. We finally illustrate the accuracy of the proposed algorithms via some test tensors from synthetic and real databases. In particular, for the fixed TT-rank problem, the proposed algorithms can be several times faster than the TT-SVD, and the accuracy of the proposed algorithms and the TT-SVD are comparable for several test *** Codes 15A18, 15A69, 65F55, 68W20 Copyright © 2024, The Authors. All rights reserved.

关键词： Tensors

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An effective model for quantification of cell 3Dshape in early embryogenesis

Research Square

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Research Square 2021年

作者： Li, Zelin Cao, Jianfeng Zhao, Zhongying Yan, Hong Center for Intelligent Multidimensional Data Analysis and Department of Electrical Engineering City University of Hong Kong Kowloon Tong Hong Kong Department of Biology Hong Kong Baptist University Kowloon Tong Hong Kong

Background: The cell developmental process is featured by fabulous morphogenesis in multicellular organisms. Describing morphological changes quantitatively concretes the way to investigating both intra and inter cell regulations on cell fate. While Caenorhabditis elegans has been used as a model for cell development studies for a long time, the research of how cell shape is precisely controlled remains obscure by the lack of methods to model morphological features. Currently, in order to characterize the features of cell shape involved in cell migration and differentiation, there is an increasing demand in analyzing cell shape systematically, especially when many works have contributed to cell reconstruction. Results: In this work, Spherical harmonics and Principal component analysis integrated Cell Shape quantification Models (SPCSMs) is proposed to represent cell shapes in a low-dimensional shape space. SPCSMs incorporates a complete pipeline to quantify cell shapes and analyze their morphological phenotypes in three dimensional (3D) reconstructions. Based on the framework, we extract biologically meaningful patterns in the lineage of C. elegans embryo before 350-cell stage, during which all hypodermis cells deformed like a funnel and can be recognized based on these shape patterns. Finally, SPCSMs is compared with two cell shape representation methods, which substantiates the effectiveness and robustness of our method. Conclusion: SPCSMs provides a general method to decribe shapes in low-dimensional shape space with compact parameters. It can quantify the shapes of cells from single-cell resolution images obtained over one-minute intervals, making it possible to recognize developmental patterns in cell lineages. SPCSMs is expected to be an effective model for biologists to explore the relationships between the shapes of cells and their fates. © 2021, CC BY.

关键词： Cells

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VARIABLE T-PRODUCT AND ZERO-PADDING TENSOR COMPLETION WITH APPLICATIONS

arXiv

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arXiv 2023年

作者： Qi, Liqun Yan, Rui Luo, Ziyan Yan, Hong Yu, Gaohang Department of Mathematics Hangzhou Dianzi University Hangzhou310018 China School of Mathematics and Statistics Beijing Jiaotong University Beijing100044 China Department of Electrical Engineering Center for Intelligent Multidimensional Data Analysis City University of Hong Kong Kowloon Hong Kong

The T-product method based upon Discrete Fourier Transformation (DFT) has found wide applications in engineering, in particular, in image processing. In this paper, we propose variable T-product, and apply the Zero-Padding Discrete Fourier Transformation (ZDFT), to convert third order tensor problems to the variable Fourier domain. An additional positive integer parameter is introduced, which is greater than the tubal dimension of the third order tensor. When the additional parameter is equal to the tubal dimension, the ZDFT reduces to DFT. Then, we propose a new tensor completion method based on ZDFT and TV regularization, called VTCTF-TV. Extensive numerical experiment results on visual data demonstrate that the superior performance of the proposed method. In addition, the zero-padding is near the size of the original tubal dimension, the resulting tensor completion can be performed much better. © 2023, CC BY.

关键词： Discrete Fourier transforms

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Domain Generalization with Small data

arXiv

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arXiv 2024年

作者： Chen, Kecheng Gal, Elena Yan, Hong Li, Haoliang Department of Electrical Engineering Center for Intelligent Multidimensional Data Analysis City University of Hong Kong Tat Chee Avenue Kowloon Hong Kong Department of Engineering University of Oxford Old Road Campus Research Building Roosevelt Drive OxfordOX3 7DQ United Kingdom

In this work, we propose to tackle the problem of domain generalization in the context of insufficient samples. Instead of extracting latent feature embeddings based on deterministic models, we propose to learn a domain-invariant representation based on the probabilistic framework by mapping each data point into probabilistic embeddings. Specifically, we first extend empirical maximum mean discrepancy (MMD) to a novel probabilistic MMD that can measure the discrepancy between mixture distributions (i.e., source domains) consisting of a series of latent distributions rather than latent points. Moreover, instead of imposing the contrastive semantic alignment (CSA) loss based on pairs of latent points, a novel probabilistic CSA loss encourages positive probabilistic embedding pairs to be closer while pulling other negative ones apart. Benefiting from the learned representation captured by probabilistic models, our proposed method can marriage the measurement on the distribution over distributions (i.e., the global perspective alignment) and the distribution-based contrastive semantic alignment (i.e., the local perspective alignment). Extensive experimental results on three challenging medical datasets show the effectiveness of our proposed method in the context of insufficient data compared with state-of-the-art methods. © 2024, CC BY.

关键词： Alignment

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Efficient algorithms for Tucker decomposition via approximate matrix multiplication

arXiv

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arXiv 2023年

作者： Che, Maolin Wei, Yimin Yan, Hong School of Mathematics Southwestern University of Finance and Economics Chengdu611130 China School of Mathematical Sciences Key Laboratory of Mathematics for Nonlinear Sciences Fudan University Shanghai200433 China Department of Electrical Engineering Center for Intelligent Multidimensional Data Analysis City University of Hong Kong 83 Tat Chee Avenue Kowloon Hong Kong

This paper develops fast and efficient algorithms for computing Tucker decomposition with a given multilinear rank. By combining random projection and the power scheme, we propose two efficient randomized versions for the truncated high-order singular value decomposition (T-HOSVD) and the sequentially T-HOSVD (ST-HOSVD), which are two common algorithms for approximating Tucker decomposition. To reduce the complexities of these two algorithms, fast and efficient algorithms are designed by combining two algorithms and approximate matrix multiplication. The theoretical results are also achieved based on the bounds of singular values of standard Gaussian matrices and the theoretical results for approximate matrix multiplication. Finally, the efficiency of these algorithms are illustrated via some test tensors from synthetic and real datasets. Copyright © 2023, The Authors. All rights reserved.

关键词： Tensors

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Undersea Cable Path Planning with Curvature Constraints

Undersea Cable Path Planning with Curvature Constraints

引用

International Conference on Transparent Optical Networks

作者： Xinyu Wang Fahan Chen Zengfu Wang Tianjiao Wang Elias Tahchi Bill Moran Moshe Zukerman Department of Electrical Engineering City University of Hong Kong Hong Kong SAR China School of Automation Northwestern Polytechnical University Xi’an China Center for Intelligent Multidimensional Data Analysis Hong Kong SAR China Fugro Germany Marine GmbH Bremen Germany Department of Electrical and Electronic Engineering University of Melbourne Victoria Australia

ISBN: (数字)9798350377323

ISBN: (纸本)9798350377330

Undersea optical fiber cables that span vast distances are integral to the Internet’s infrastructure. Manual path planning of such cables is an arduous task. The Fast Marching Method (FMM), a precise numerical approach capable of solving the Eikonal equation, offers a viable, rigorous, and efficient alternative by optimizing the path between source and destination, taking account of a summary objective function of costs and risk factors. However, its implementation often neglects the crucial curvature constraints arising from the flexural rigidity of cables and maneuvering capabilities of the laying vessels in real-world scenarios. In an attempt to address this issue in real-world cable path planning, our work incorporates these constraints. We propose modifying our previous FMM-based work to generate paths by systematically expanding forbidden regions and replacing sharp angular changes with circular arcs of a predefined radius to ensure compliance with the curvature constraints. By factoring curvature into cable system design, we ensure robust, real-world applicability of cable path design methods. While this modification may result in a departure from the FMM’s optimally calculated path, potentially compromising its cost-effectiveness or risk minimization, the adjusted route adheres to essential curvature constraints and the structural integrity of cables. A more rigorously optimal approach to curvature is possible, but its implementation in our context appears to be difficult and does not appear to yield significant improvements.

关键词： Costs Risk minimization Optical fiber cables Optical fiber networks Path planning Mathematical models Rigidity

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A regularization-patching dual quaternion optimization method for solving the hand-eye calibration problem

arXiv

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arXiv 2022年

作者： Chen, Zhongming Ling, Chen Qi, Liqun Yan, Hong Department of Mathematics School of Science Hangzhou Dianzi University Hangzhou310018 China Department of Applied Mathematics The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong Center for Intelligent Multidimensional Data Analysis Science Park Shatin Hong Kong Department of Electrical Engineering City University of Hong Kong Kowloon Hong Kong

The hand-eye calibration problem is an important application problem in robot research. Based on the 2-norm of dual quaternion vectors, we propose a new dual quaternion optimization method for the hand-eye calibration problem. The dual quaternion optimization problem is decomposed to two quaternion optimization subproblems. The first quaternion optimization subproblem governs the rotation of the robot hand. It can be solved efficiently by the eigenvalue decomposition or singular value decomposition. If the optimal value of the first quaternion optimization subproblem is zero, then the system is rotationwise noiseless, i.e., there exists a "perfect" robot hand motion which meets all the testing poses rotationwise exactly. In this case, we apply the regularization technique for solving the second subproblem to minimize the distance of the translation. Otherwise we apply the patching technique to solve the second quaternion optimization subproblem. Then solving the second quaternion optimization subproblem turns out to be solving a quadratically constrained quadratic program. In this way, we give a complete description for the solution set of hand-eye calibration problems. This is new in the hand-eye calibration literature. The numerical results are also presented to show the efficiency of the proposed method. © 2022, CC BY.

关键词： Numerical methods

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QR Decomposition of Dual Matrices and its Application to Traveling Wave Identification in the Brain

arXiv

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arXiv 2024年

作者： Xu, Renjie Wei, Tong Wei, Yimin Xie, Pengpeng Center for Intelligent Multidimensional Data Analysis Hong Kong Science Park Shatin Hong Kong Institute of Science and Technology for Brain-Inspired Intelligence Fudan University Shanghai200433 China School of Mathematical Sciences Shanghai Key Laboratory of Contemporary Applied Mathematics Fudan University Shanghai200433 China School of Mathematical Sciences Ocean University of China Qingdao266100 China

Matrix decompositions in dual number representations have played an important role in fields such as kinematics and computer graphics in recent years. In this paper, we present a QR decomposition algorithm for dual number matrices, specifically geared towards its application in traveling wave identification, utilizing the concept of proper orthogonal decomposition. When dealing with large-scale problems, we present explicit solutions for the QR, thin QR, and randomized QR decompositions of dual number matrices, along with their respective algorithms with column pivoting. The QR decomposition of dual matrices is an accurate first-order perturbation, with the Q-factor satisfying rigorous perturbation bounds, leading to enhanced orthogonality. In numerical experiments, we discuss the suitability of different QR algorithms when confronted with various large-scale dual matrices, providing their respective domains of applicability. Subsequently, we employed the QR decomposition of dual matrices to compute the DMPGI, thereby attaining results of higher precision. Moreover, we apply the QR decomposition in the context of traveling wave identification, employing the notion of proper orthogonal decomposition to perform a validation analysis of large-scale functional magnetic resonance imaging (fMRI) data for brain functional circuits. Our approach significantly improves the identification of two types of wave signals compared to previous research, providing empirical evidence for cognitive neuroscience theories. Copyright © 2024, The Authors. All rights reserved.

关键词： Brain

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