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The Giga-pixel Challenge: Full Resolution Image Analysis – Without Losing the Big Picture: An open-source approach for multi-scale analysis and visualization of slide-scanner data
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. (Quantitative Microscopy)ORCID iD: 0000-0002-6699-4015
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
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2014 (English)Conference paper, Oral presentation only (Other academic)
Abstract [en]

The amount of image data in a slide scanner image is usually in the giga-pixel range, inducing challenges for image analysis and visualization. At the same time, in order to maximize the information gained in these experi-ments and integrate expert knowledge with quantitative measurements, it is crucial to maintain the connection be-tween high-resolution per-cell and per-region metrics with lower resolution relational metrics. We present a free and open-source framework for full resolution image analysis of large images, e.g. slide scanner data, with the possibility of visual examination and interaction at multiple resolutions. The interface enables seamless zooming and panning, with the option to toggle multiple layers, such as segmentation masks and classification results, on or off. We make use of the strength and flexibility of existing state-of-the-art open-source software for visualization, creating resolution pyra-mids, image registration and image analysis.

Place, publisher, year, edition, pages
2014.
Keyword [en]
multi-scale image analysis, slide scanner data, open source
National Category
Other Computer and Information Science
Research subject
Computerized Image Processing
Identifiers
URN: urn:nbn:se:uu:diva-234960OAI: oai:DiVA.org:uu-234960DiVA: diva2:758499
Conference
SSBA 2014, Symposium of the Swedish Society for Automated Image Analysis, 10-12 March, 2014, Luleå, Sweden
Available from: 2014-10-27 Created: 2014-10-27 Last updated: 2014-10-29Bibliographically approved

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fulltext(859 kB)203 downloads
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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • vancouver
  • Other style
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Language
  • de-DE
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  • nn-NB
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More languages
Output format
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