Suppr超能文献

ImageJ生态系统:一个用于生物医学图像分析的开放平台。

The ImageJ ecosystem: An open platform for biomedical image analysis.

作者信息

Schindelin Johannes, Rueden Curtis T, Hiner Mark C, Eliceiri Kevin W

机构信息

Laboratory for Optical and Computational Instrumentation, University of Wisconsin at Madison, Madison, Wisconsin.

出版信息

Mol Reprod Dev. 2015 Jul-Aug;82(7-8):518-29. doi: 10.1002/mrd.22489. Epub 2015 Jul 7.

Abstract

Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available-from commercial to academic, special-purpose to Swiss army knife, small to large-but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on the life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts the life sciences, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem.

摘要

显微镜技术发展迅速,使得定量生物医学成像越来越经济实惠、速度更快且更精确,这相应地需要更先进的图像处理和分析技术。有各种各样的软件可供使用——从商业软件到学术软件,从专用软件到多功能软件,从小型软件到大型软件——但适合科学探究的软件的一个关键特性是其可获取性。开源软件对于科学研究来说是理想之选,因为它可以被自由检查、修改和重新分发;特别是,开源软件平台ImageJ对生命科学产生了巨大影响,并且仍在持续发挥作用。从一开始,ImageJ就有了显著发展,这在很大程度上得益于其免费可得以及活跃且乐于助人的用户社区。从感兴趣的业余爱好者、技术助理、学生、科研人员到高级生物学研究人员等各种各样的科学家每天都在使用ImageJ,并通过其专门的邮件列表交流知识。ImageJ的用途广泛,从数据可视化和教学到高级图像处理和统计分析。该软件的可扩展性持续吸引着各个职业阶段的生物学家以及希望有效实现特定图像处理算法的计算机科学家。在本综述中,我们以ImageJ项目为例,研究开源软件如何培育其软件工具套件,使科学界能够轻松获取大量图像分析技术。我们具体探讨是什么让ImageJ如此受欢迎,它如何影响生命科学,它如何启发其他项目,以及它如何受到ImageJ生态系统中共同发展的项目的自我影响。

相似文献

1
The ImageJ ecosystem: An open platform for biomedical image analysis.
Mol Reprod Dev. 2015 Jul-Aug;82(7-8):518-29. doi: 10.1002/mrd.22489. Epub 2015 Jul 7.
2
ImageJ2: ImageJ for the next generation of scientific image data.
BMC Bioinformatics. 2017 Nov 29;18(1):529. doi: 10.1186/s12859-017-1934-z.
3
The ImageJ ecosystem: Open-source software for image visualization, processing, and analysis.
Protein Sci. 2021 Jan;30(1):234-249. doi: 10.1002/pro.3993. Epub 2020 Nov 20.
4
Integration of the ImageJ Ecosystem in the KNIME Analytics Platform.
Front Comput Sci. 2020 Mar;2. doi: 10.3389/fcomp.2020.00008. Epub 2020 Mar 17.
5
New Extensibility and Scripting Tools in the ImageJ Ecosystem.
Curr Protoc. 2021 Aug;1(8):e204. doi: 10.1002/cpz1.204.
6
Quantitating the cell: turning images into numbers with ImageJ.
Wiley Interdiscip Rev Dev Biol. 2017 Mar;6(2). doi: 10.1002/wdev.260. Epub 2016 Dec 2.
7
Easing batch image processing from OMERO: a new toolbox for ImageJ.
F1000Res. 2022 Apr 5;11:392. doi: 10.12688/f1000research.110385.2. eCollection 2022.
10
ImageJ in Computational Fractal-Based Neuroscience: Pattern Extraction and Translational Research.
Adv Neurobiol. 2024;36:795-814. doi: 10.1007/978-3-031-47606-8_40.

引用本文的文献

1
The impact of shade on whole-plant carbon allocation in a dominant East African tree sapling.
AoB Plants. 2025 Jul 30;17(4):plaf039. doi: 10.1093/aobpla/plaf039. eCollection 2025 Aug.
3
Structure and function of the ovipositor of the encyrtid wasp Microterys flavus.
Front Zool. 2025 Aug 25;22(1):24. doi: 10.1186/s12983-025-00575-1.
4
Regulation of EMT-MET and chemoresistance by the Lc3Cer-synthase B3GNT5.
BMC Cancer. 2025 Aug 22;25(1):1356. doi: 10.1186/s12885-025-14717-5.
5
Getting under the skin of the menopausal hot flush: a protocol to examine skin function and structure in symptomatic postmenopausal women.
Front Glob Womens Health. 2025 Aug 4;6:1514960. doi: 10.3389/fgwh.2025.1514960. eCollection 2025.
6
Advanced Feature Extraction and Outlier Detection for 3D Biological/Biomedical Image Registration.
IEEE Trans Comput Biol Bioinform. 2025 Jul-Aug;22(4):1335-1346. doi: 10.1109/TCBBIO.2024.3517596.
10
An image analysis pipeline to quantify the spatial distribution of cell markers in stroma-rich tumors.
bioRxiv. 2025 May 1:2025.04.28.650414. doi: 10.1101/2025.04.28.650414.

本文引用的文献

1
Preface. Digital microscopy.
Methods Cell Biol. 2013;114:xix-xx. doi: 10.1016/B978-0-12-407761-4.09952-8.
2
OpenSPIM: an open-access light-sheet microscopy platform.
Nat Methods. 2013 Jul;10(7):598-9. doi: 10.1038/nmeth.2507. Epub 2013 Jun 9.
3
Endrov: an integrated platform for image analysis.
Nat Methods. 2013 Jun;10(6):454-6. doi: 10.1038/nmeth.2478.
4
ImgLib2--generic image processing in Java.
Bioinformatics. 2012 Nov 15;28(22):3009-11. doi: 10.1093/bioinformatics/bts543. Epub 2012 Sep 8.
5
NIH Image to ImageJ: 25 years of image analysis.
Nat Methods. 2012 Jul;9(7):671-5. doi: 10.1038/nmeth.2089.
6
Biological imaging software tools.
Nat Methods. 2012 Jun 28;9(7):697-710. doi: 10.1038/nmeth.2084.
7
Icy: an open bioimage informatics platform for extended reproducible research.
Nat Methods. 2012 Jun 28;9(7):690-6. doi: 10.1038/nmeth.2075.
8
Fiji: an open-source platform for biological-image analysis.
Nat Methods. 2012 Jun 28;9(7):676-82. doi: 10.1038/nmeth.2019.
9
TrakEM2 software for neural circuit reconstruction.
PLoS One. 2012;7(6):e38011. doi: 10.1371/journal.pone.0038011. Epub 2012 Jun 19.
10
Visualization and analysis of 3D microscopic images.
PLoS Comput Biol. 2012;8(6):e1002519. doi: 10.1371/journal.pcbi.1002519. Epub 2012 Jun 14.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验