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Automatic Cell Identification in the Unique System of Invariant Embryogenesis in Caenorhabditis elegans

BIOMEDICAL ENGINEERING LETTERS 2014年第4期4卷 328-337页

作者： Azuma, Yusuke Onami, Shuichi RIKEN Quantitat Biol Ctr Lab Dev Dynam Kobe Hyogo 6500047 Japan Japan Sci & Technol Agcy Natl Biosci Database Ctr Tokyo 1020081 Japan

In recent years, development of image processing methods has rapidly progressed to automatically identify spatiotemporal dynamics of embryonic cells in Caenorhabditis elegans. The methods allow quantitative and high-throughput analysis for molecular dynamics during embryogenesis. In turn, the analyzed dynamics can be merged onto a reference embryo, providing an integrated view of embryogenesis. This integration is enabled by invariant embryogenesis of C. elegans, which is the most unique advantage offered by this organism. Therefore, the key point in the development of the methods is how to take advantage of this feature. In this article, we review a series of development of such methods and their applications. First, we describe basic image processing methods that are the basis for development of cell identification methods. Next, we describe methods that have succeeded to identify cells in images and their performance. Finally, we review studies that have employed cell identification methods to analyze the variability of cellular dynamics, cell-cell contacts and cell fate determination. Together with advances in imaging technologies to measure molecular dynamics and computational methods to identify such dynamics with high accuracy, the unique system of invariant embryogenesis in C. elegans will be invaluable to study developmental mechanisms. Therefore, it is important to understand the ever developing technologies and their results.

关键词： bioimage informatics Image processing Cell tracking Caenorhabditis elegans

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The Demand for Quantitative Techniques in Biomedical Image informatics

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BIOMEDICAL ENGINEERING LETTERS 2014年第4期4卷 319-327页

作者： Jang, Ha-Young Kim, Hye-Ryun Kang, Mi-Sun Kim, Myoung-Hee Zhang, Byoung-Tak Seoul Natl Univ Dept Comp Sci & Engn Seoul South Korea Ewha Womans Univ Dept Comp Sci & Engn Seoul 120750 South Korea

With recent technological advances, biomedical image informatics has become a quickly rising field. It focuses on the use of computational techniques to process and analyze biomedical images. Its goal is to obtain useful knowledge from complicated and heterogeneous images from different modalities for biomedical research. Although the advancement of imaging technologies has provided a data explosion, most biomedical images are only used by the researchers who create them. The lack of a canonical procedure, from data acquisition to data analysis, contributes to this issue. As the number of biomedical images increases, the demand for quantitative techniques rises. In order to increase awareness of the needs and importance of quantitative techniques for biomedical image informatics, this paper reviews several aspects including biomedical imaging, image repositories, and image processing. We explore the state of the art technology available in quantitative techniques for biomedical image informatics. The essential techniques for quantification, such as imaging devices, biomedical image management, and image processing, are further summarized.

关键词： Biomedical image informatics Quantitative imaging bioimage informatics Imaging informatics

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Automated Neuron Tracing Methods: An Updated Account

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NEUROinformatics 2016年第4期14卷 353-367页

作者： Acciai, Ludovica Soda, Paolo Iannello, Giulio Univ Campus Biomed Rome Dept Engn Rome Italy

The reconstruction of neuron morphology allows to investigate how the brain works, which is one of the foremost challenges in neuroscience. This process aims at extracting the neuronal structures from microscopic imaging data. The great advances in microscopic technologies have made a huge amount of data available at the micro-, or even lower, resolution where manual inspection is time consuming, prone to error and utterly impractical. This has motivated the development of methods to automatically trace the neuronal structures, a task also known as neuron tracing. This paper surveys the latest neuron tracing methods available in the scientific literature as well as a selection of significant older papers to better place these proposals into context. They are categorized into global processing, local processing and meta-algorithm approaches. Furthermore, we point out the algorithmic components used to design each method and we report information on the datasets and the performance metrics used.

关键词： Neuron tracing Neuron morphology Digital reconstruction bioimage informatics Neuroscience BigNeuron

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Neuron Tracing in Perspective

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CYTOMETRY PART A 2010年第7期77A卷 693-704页

作者： Meijering, Erik Univ Med Ctr Rotterdam Biomed Imaging Grp Rotterdam Erasmus MC NL-3000 CA Rotterdam Netherlands

The study of the structure and function of neuronal cells and networks is of crucial importance in the endeavor to understand how the brain works. A key component in this process is the extraction of neuronal morphology nom microscopic Imaging data In the past four decades, many computational methods and tools have been developed for digital reconstruction of neurons from images, with limited success. As witnessed by the growing body of literature on the subject, as well as the organization of challenging competitions in the field, the quest for a robust and fully automated system of more general applicability still continues The aim of this work, is to contribute by surveying recent developments in the field for anyone interested in taking up the challenge. Relevant aspects discussed in the article include proposed image segmentation methods, quantitative measures of neuronal morphology, currently available software tools for various related purposes, and morphology databases (C) 2010 International Society for Advancement of Cytometry

关键词： neuron tracing, digital reconstruction, image segmentation quantitative image analysis, pattern recognition bioimage informatics neuroinformatics, neuroscience, software, tools databases

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Image processing and recognition for biological images

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DEVELOPMENT GROWTH & DIFFERENTIATION 2013年第4期55卷 523-549页

作者： Uchida, Seiichi Kyushu Univ Dept Adv Informat Technol Nishi Ku Fukuoka 8190395 Japan

This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target.

关键词： bioimage informatics image pattern recognition image processing

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ICY: A USER-FRIENDLY ENVIRONMENT FOR ALGORITHM DEVELOPMENT AND DEPLOYMENT

ICY: A USER-FRIENDLY ENVIRONMENT FOR ALGORITHM DEVELOPMENT A...

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21st European Signal Processing Conference (EUSIPCO)

作者： de Chaumont, Fabrice Dallongeville, Stephane Provoost, Thomas Lecomte, Timothee Dufour, Alexandre Olivo-Marin, Jean-Christophe Inst Pasteur Quantitat Image Anal Unit CNRS URA 2582 F-75015 Paris France

ISBN: (纸本)9780992862602

bioimage informatics has emerged as a new interdisciplinary research endeavor for bringing the power of computational and mathematical sciences into the biological imaging arena. We describe an open-source software platform, Icy, that proposes a comprehensive framework for easy algorithm development and deployment fostering community-oriented efforts. Icy offers a platform to share and publish collaborative algorithm developments, while promoting re-usability and code sharing to ease the development of new algorithms, and simplifying user's feedback and support through a community web site.

关键词： bioimage informatics open source automated image acquisition Java visual programming script reproducible research

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BENCHMARKING IMAGE-PROCESSING ALGORITHMS FOR BIOMICROSCOPY: REFERENCE DATASETS AND PERSPECTIVES

BENCHMARKING IMAGE-PROCESSING ALGORITHMS FOR BIOMICROSCOPY: ...

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21st European Signal Processing Conference (EUSIPCO)

作者： Sage, Daniel Kirshner, Hagai Vonesch, Cedric Lefkimmiatis, Stamatios Unser, Michael Ecole Polytech Fed Lausanne Biomed Imaging Grp CH-1015 Lausanne Switzerland

ISBN: (纸本)9780992862602

As the field of bioimage informatics matures, the issue of the validation of image reconstruction algorithms and the definition of proper performance criteria becomes more pressing. In this work, we discuss benchmarking aspects of fluorescence microscopy quantitative tools. We point out the importance of generating realistic datasets and describe our approach to this task. We rely on our experience and present arguments in favor of the use of 3D continuous-domain models of biological structures for simulating bioimaging datasets. We also present physically-realistic models of image formation that that are reasonably efficiently to implement.

关键词： bioimage informatics fluorescence microscopy benchmarking simulated datastets

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Stable Marriage Algorithm for Tracking Intracellular Objects

Stable Marriage Algorithm for Tracking Intracellular Objects

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1st International Symposium on Computing and Networking (CANDAR)

作者： Hamano, Ayumi Fujisaki, Kensho Uchida, Seiichi Shiku, Osamu Kyushu Univ Grad Sch Syst Life Sci Fukuoka 812 Japan Sasebo Natl Coll Tech Dept Control Engn Nagasaki Japan

ISBN: (纸本)9781479927951

Development of automatic multiple intracellular-objects tracking methods is one of the significant challenges in bioimage-informatics. The challenge becomes more difficult in case the tracking targets have the same shape and appearance. In order to obtain stable results under that condition, we propose a tracking method based on global optimization. Particularly, we first detect tracking targets by our proposed detection method. Then, we formulate the multiple object tracking problem as a combinatorial optimization problem over a pair of consecutive frames. Finally, we solve the problem by the stable marriage algorithm. In this paper, we describe our proposed detection and tracking methods.

关键词： Multiple object tracking Object detection Stable marriage problem bioimage informatics

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LOCAL PHASE APPROACHES TO EXTRACT BIOMEDICAL NETWORKS

LOCAL PHASE APPROACHES TO EXTRACT BIOMEDICAL NETWORKS

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9th IEEE International Symposium on Biomedical Imaging (ISBI) - From Nano to Macro

作者： Obara, Boguslaw Fricker, Mark Grau, Vicente Univ Oxford Oxford E Res Ctr Oxford OX1 2JD England Univ Oxford Oxford Ctr Integrat Syst Biol Oxford England Univ Oxford Dept Plant Sci Oxford England Univ Oxford Inst Biomed Engn Oxford England

ISBN: (纸本)9781457718588

Many biomedical applications require detection of curvilinear networks in images, and would benefit from automatic or semiautomatic segmentation to allow high-throughput measurements. Here we discuss a contrast independent approach to identify curvilinear structures based on oriented phase congruency, the Phase Congruency Tensor. We show that the proposed approach is largely insensitive to intensity variations along the curve, and provides successful detection within noisy regions. Moreover, we demonstrate that the proposed approach may be used in a wide range of curvilinear and non-curvilinear feature enhancement and detection methods, particularly where tensor representation of the image is explored. The performance of the Phase Congruency Tensor-based methods is evaluated by comparing it with state-of-the-art intensity-based methods on both synthetic and real images of biomedical networks.

关键词： bioimage informatics Phase Congruency Tensor curvilinear structure branching structure live-wire tracing feature detection vector field directional statistics blob detector anisotropic diffusion filtering coherence enhancing biomedical networks

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Detection and Tracking Protein Molecules in Fluorescence Microscopic Video

Detection and Tracking Protein Molecules in Fluorescence Mic...

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1st International Symposium on Computing and Networking (CANDAR)

作者： Fujisaki, Kensho Hamano, Ayumi Aoki, Kenta Feng, Yaokai Uchida, Seiichi Araseki, Masahiko Saito, Yuki Suzuki, Toshiharu Kyushu Univ Dept Adv Informat Technol Fukuoka 812 Japan

ISBN: (纸本)9781479927951

This paper provides a bioimage informatics system of detecting and tracking protein molecules, called APP-GFPs, in a live-cell video captured by a fluorescent microscope. Since both processes encounter many difficulties such as many targets, less appearance information, and heavy background noise, we will try to design the system as robust as possible. Specifically, for the detection, a machine learning-based method is employed. For tracking, a method based on a global optimization strategy is newly developed. Experimental results showed that the speed and direction distributions of molecular motion by the proposed system were very similar to that by manual inspection.

关键词： Object detection Multi-target object tracking Offline tracking bioimage informatics Fluorescent microscope

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