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- Dobson, Ellen T.A., et al.
(author)
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ImageJ and CellProfiler : Complements in Open‐Source Bioimage Analysis
- 2021
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In: Current Protocols in Microbiology. - : John Wiley & Sons. - 1934-8525 .- 1088-7423. ; 1:5
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Journal article (peer-reviewed)abstract
- ImageJ and CellProfiler have long been leading open-source platforms in the field of bioimage analysis. ImageJ's traditional strength is in single-image processing and investigation, while CellProfiler is designed for building large-scale, modular analysis pipelines. Although many image analysis problems can be well solved with one or the other, using these two platforms together in a single workflow can be powerful. Here, we share two pipelines demonstrating mechanisms for productively and conveniently integrating ImageJ and CellProfiler for (1) studying cell morphology and migration via tracking, and (2) advanced stitching techniques for handling large, tiled image sets to improve segmentation. No single platform can provide all the key and most efficient functionality needed for all studies. While both programs can be and are often used separately, these pipelines demonstrate the benefits of using them together for image analysis workflows. ImageJ and CellProfiler are both committed to interoperability between their platforms, with ongoing development to improve how both are leveraged from the other
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| 2. |
- Ouyang, Wei, et al.
(author)
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Moving beyond the desktop: prospects for practical bioimage analysis via the web
- 2023
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In: Frontiers in Bioinformatics. - : Frontiers Media SA. - 2673-7647. ; 3
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Journal article (peer-reviewed)abstract
- As biological imaging continues to rapidly advance, it results in increasingly complex image data, necessitating a reevaluation of conventional bioimage analysis methods and their accessibility. This perspective underscores our belief that a transition from desktop-based tools to web-based bioimage analysis could unlock immense opportunities for improved accessibility, enhanced collaboration, and streamlined workflows. We outline the potential benefits, such as reduced local computational demands and solutions to common challenges, including software installation issues and limited reproducibility. Furthermore, we explore the present state of web-based tools, hurdles in implementation, and the significance of collective involvement from the scientific community in driving this transition. In acknowledging the potential roadblocks and complexity of data management, we suggest a combined approach of selective prototyping and large-scale workflow application for optimal usage. Embracing web-based bioimage analysis could pave the way for the life sciences community to accelerate biological research, offering a robust platform for a more collaborative, efficient, and democratized science.
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