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TissueWand, a rapid...
TissueWand, a rapid histopathology annotation tool
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- Lindvall, Martin (author)
- Linköpings universitet,Medie- och Informationsteknik,Tekniska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Sectra AB
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- Sanner, Alexander (author)
- Sectra AB, Research Department, Linköping, Sweden
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- Petré, Fredrik (author)
- Sectra AB, Research Department, Linköping, Sweden
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- Lindman, Karin, 1980- (author)
- Linköpings universitet,Avdelningen för neurobiologi,Medicinska fakulteten,Region Östergötland, Klinisk patologi
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- Treanor, Darren, 1974- (author)
- Linköpings universitet,Avdelningen för inflammation och infektion,Medicinska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Region Östergötland, Klinisk patologi,University of Leeds, Leeds, UK
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- Lundström, Claes, 1973- (author)
- Linköpings universitet,Medie- och Informationsteknik,Tekniska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Sectra AB
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- Löwgren, Jonas, 1964- (author)
- Linköpings universitet,Medie- och Informationsteknik,Tekniska fakulteten
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(creator_code:org_t)
- Medknow Publications, 2020
- 2020
- English.
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In: Journal of Pathology Informatics. - : Medknow Publications. - 2229-5089 .- 2153-3539. ; 11:27
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https://liu.diva-por... (primary) (Raw object)
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Abstract
Subject headings
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- Background: Recent advancements in machine learning (ML) bring great possibilities for the development of tools to assist with diagnostic tasks within histopathology. However, these approaches typically require a large amount of ground truth training data in the form of image annotations made by human experts. As such annotation work is a very time-consuming task, there is a great need for tools that can assist in this process, saving time while not sacrificing annotation quality. Methods: In an iterative design process, we developed TissueWand – an interactive tool designed for efficient annotation of gigapixel-sized histopathological images, not being constrained to a predefined annotation task. Results: Several findings regarding appropriate interaction concepts were made, where a key design component was semi-automation based on rapid interaction feedback in a local region. In a user study, the resulting tool was shown to cause substantial speed-up compared to manual work while maintaining quality. Conclusions: The TissueWand tool shows promise to replace manual methods for early stages of dataset curation where no task-specific ML model yet exists to aid the effort.
Subject headings
- HUMANIORA -- Konst -- Design (hsv//swe)
- HUMANITIES -- Arts -- Design (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Människa-datorinteraktion (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Human Computer Interaction (hsv//eng)
Keyword
- Annotation
- digital pathology
- usability
- user interface design
- machine learning
Publication and Content Type
- ref (subject category)
- art (subject category)
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- By the author/editor
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Lindvall, Martin
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Sanner, Alexande ...
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Petré, Fredrik
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Lindman, Karin, ...
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Treanor, Darren, ...
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Lundström, Claes ...
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show more...
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Löwgren, Jonas, ...
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- About the subject
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- HUMANITIES
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HUMANITIES
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and Arts
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and Design
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Computer and Inf ...
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and Human Computer I ...
- Articles in the publication
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Journal of Patho ...
- By the university
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Linköping University