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- Rydell, Christopher (author)
CytoBrowser: a browser-based collaborative annotation platform for whole slide images
- Article/chapterEnglish2021
Publisher, publication year, extent ...
- 2021-03-22
- F1000 Research Ltd,2021
- printrdacarrier
Numbers
- LIBRIS-ID:oai:DiVA.org:uu-457604
- https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-457604URI
- https://doi.org/10.12688/f1000research.51916.1DOI
Supplementary language notes
- Language:English
- Summary in:English
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- SwePubSwePub
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Notes
- We present CytoBrowser, an open-source (GPLv3) JavaScript and Node.js driven environment for fast and accessible collaborative online visualization, assessment, and annotation of very large microscopy images, including, but not limited to, z-stacks (focus stacks) of cytology or histology whole slide images. CytoBrowser provides a web-based viewer for high-resolution zoomable images and facilitates easy remote collaboration, with options for joint-view visualization and simultaneous collaborative annotation of very large datasets. It delivers a unique combination of functionalities not found in other software solutions, making it a preferred tool for large scale annotation of whole slide image data. The web browser interface is directly accessible on any modern computer or even on a mobile phone, without need for additional software. By sharing a "session", several remote users can interactively explore and jointly annotate whole slide image data, thereby reaching improved data understanding and annotation quality, effortless project scaling and distribution of resources to/from remote locations, efficient creation of "ground truth" annotations for methods' evaluation and training of machine learning-based approaches, a user-friendly learning environment for medical students, to just name a few. Rectangle and polygon region annotations complement point-based annotations, each with a selectable annotation-class as well as free-form text fields. The default setting of CytoBrowser presents an interface for the Bethesda cancer grading system, while other annotation schemes can easily be incorporated. Automatic server side storage of annotations is complemented by JSON-based import/export options facilitating easy interoperability with other tools. CytoBrowser is available here: https://mida-group.github.io/CytoBrowser/.
Subject headings and genre
- TEKNIK OCH TEKNOLOGIER Medicinteknik Medicinsk bildbehandling hsv//swe
- ENGINEERING AND TECHNOLOGY Medical Engineering Medical Image Processing hsv//eng
- virtual microscopy
- digital cytology
- whole slide image
- annotation
- assessment
- visualization
- bioimage informatics
- JavaScript
- Computerized Image Processing
- Datoriserad bildbehandling
Added entries (persons, corporate bodies, meetings, titles ...)
- Lindblad, JoakimUppsala universitet,Bildanalys och människa-datorinteraktion,Avdelningen för visuell information och interaktion,MIDA(Swepub:uu)joali534 (author)
- Uppsala universitetBildanalys och människa-datorinteraktion (creator_code:org_t)
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- In:F1000 Research: F1000 Research Ltd102046-1402
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