Bridging imaging users to imaging analysis – A community survey

IF 1.5 4区 工程技术 Q3 MICROSCOPY
Suganya Sivagurunathan, Stefania Marcotti, Carl J Nelson, Martin L Jones, David J Barry, Thomas J A Slater, Kevin W Eliceiri, Beth A Cimini
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引用次数: 0

Abstract

The ‘Bridging Imaging Users to Imaging Analysis’ survey was conducted in 2022 by the Center for Open Bioimage Analysis (COBA), BioImaging North America (BINA) and the Royal Microscopical Society Data Analysis in Imaging Section (RMS DAIM) to understand the needs of the imaging community. Through multichoice and open-ended questions, the survey inquired about demographics, image analysis experiences, future needs and suggestions on the role of tool developers and users. Participants of the survey were from diverse roles and domains of the life and physical sciences. To our knowledge, this is the first attempt to survey cross-community to bridge knowledge gaps between physical and life sciences imaging. Survey results indicate that respondents' overarching needs are documentation, detailed tutorials on the usage of image analysis tools, user-friendly intuitive software, and better solutions for segmentation, ideally in a format tailored to their specific use cases. The tool creators suggested the users familiarise themselves with the fundamentals of image analysis, provide constant feedback and report the issues faced during image analysis while the users would like more documentation and an emphasis on tool friendliness. Regardless of the computational experience, there is a strong preference for ‘written tutorials’ to acquire knowledge on image analysis. We also observed that the interest in having ‘office hours’ to get an expert opinion on their image analysis methods has increased over the years. The results also showed less-than-expected usage of online discussion forums in the imaging community for solving image analysis problems. Surprisingly, we also observed a decreased interest among the survey respondents in deep/machine learning despite the increasing adoption of artificial intelligence in biology. In addition, the community suggests the need for a common repository for the available image analysis tools and their applications. The opinions and suggestions of the community, released here in full, will help the image analysis tool creation and education communities to design and deliver the resources accordingly.

将图像用户连接到图像分析-一项社区调查。
2022年,开放生物图像分析中心(COBA)、北美生物成像中心(BINA)和皇家显微镜学会成像数据分析科(RMS DAIM)进行了“将成像用户与成像分析联系起来”调查,以了解成像社区的需求。通过多项选择和开放式问题,调查询问了人口统计、图像分析体验、未来需求以及对工具开发人员和用户角色的建议。调查的参与者来自生命科学和物理科学的不同角色和领域。据我们所知,这是首次尝试调查跨社区,以弥合物理科学和生命科学成像之间的知识差距。调查结果表明,受访者的首要需求是文档、图像分析工具使用的详细教程、用户友好的直观软件以及更好的分割解决方案,最好是根据他们的具体用例定制的格式。工具创建者建议用户熟悉图像分析的基本原理,提供持续的反馈,并报告图像分析过程中面临的问题,同时用户希望获得更多文档并强调工具友好性。无论计算经验如何,人们都强烈倾向于“书面教程”来获取图像分析知识。我们还观察到,多年来,人们对利用“办公时间”就他们的图像分析方法获得专家意见的兴趣有所增加。结果还显示,在图像社区中,在线讨论论坛用于解决图像分析问题的使用率低于预期。令人惊讶的是,尽管人工智能在生物学中的应用越来越多,但我们还观察到调查对象对深度/机器学习的兴趣下降。此外,社区建议需要为可用的图像分析工具及其应用程序建立一个通用存储库。社区的意见和建议在这里完整发布,将有助于图像分析工具创建和教育社区相应地设计和交付资源。这篇文章受版权保护。保留所有权利。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of microscopy
Journal of microscopy 工程技术-显微镜技术
CiteScore
4.30
自引率
5.00%
发文量
83
审稿时长
1 months
期刊介绍: The Journal of Microscopy is the oldest journal dedicated to the science of microscopy and the only peer-reviewed publication of the Royal Microscopical Society. It publishes papers that report on the very latest developments in microscopy such as advances in microscopy techniques or novel areas of application. The Journal does not seek to publish routine applications of microscopy or specimen preparation even though the submission may otherwise have a high scientific merit. The scope covers research in the physical and biological sciences and covers imaging methods using light, electrons, X-rays and other radiations as well as atomic force and near field techniques. Interdisciplinary research is welcome. Papers pertaining to microscopy are also welcomed on optical theory, spectroscopy, novel specimen preparation and manipulation methods and image recording, processing and analysis including dynamic analysis of living specimens. Publication types include full papers, hot topic fast tracked communications and review articles. Authors considering submitting a review article should contact the editorial office first.
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