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Semi-automatic Training Data Generation for Cell Segmentation Network Using an Intermediary Curator Net
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
2017 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In this work we create an image analysis pipeline to segment cells from microscopy image data. A portion of the segmented images are manually curated and this curated data is used to train a Curator network to filter the whole dataset. The curated data is used to train a separate segmentation network to improve the cell segmentation. This technique can be easily applied to different types of microscopy object segmentation.

Place, publisher, year, edition, pages
2017. , p. 43
Series
UPTEC F, ISSN 1401-5757 ; 17054
Keyword [en]
Deep Learning, Bildanalys, Image Analysis, Neural Network
National Category
Other Computer and Information Science
Identifiers
URN: urn:nbn:se:uu:diva-332724OAI: oai:DiVA.org:uu-332724DiVA, id: diva2:1153920
Educational program
Master Programme in Engineering Physics
Presentation
2017-10-12, Ångström 4006, Lägerhyddsvägen 1, Uppsala, 00:19 (English)
Supervisors
Examiners
Available from: 2017-11-09 Created: 2017-11-01 Last updated: 2018-01-13Bibliographically approved

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Type fulltextMimetype application/pdf

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
  • html
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