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Intravenous bag monitoring with Convolutional Neural Networks
Linköping University, Department of Computer and Information Science.
Linköping University, Department of Computer and Information Science.
2018 (English)Independent thesis Basic level (degree of Bachelor), 10,5 credits / 16 HE creditsStudent thesis
Abstract [en]

Drip bags are used in hospital environments to administerdrugs and nutrition to patients. Ensuring that they are usedcorrectly and are refilled in time are important for the safetyof patients. This study examines the use of a ConvolutionalNeural Network (CNN) to monitor the fluid levels of drip bagsvia image recognition to potentially form the base of an earlywarning system, and assisting in making medical care moreefficient. Videos of drip bags were recorded as they wereemptying their contents in a controlled environment and fromdifferent angles. A CNN was built to analyze the recordeddata in order to predict a bags fluid level with a 5% intervalprecision from a given image. The results show that the CNNused performs poorly when monitoring fluid levels in dripbags.

Place, publisher, year, edition, pages
2018. , p. 12
Keywords [en]
Machine learning, CNN, TensorFlow, Image recognition
National Category
Information Systems
Identifiers
URN: urn:nbn:se:liu:diva-148449ISRN: LIU-IDA/LITH-EX-G--2018/048--SEOAI: oai:DiVA.org:liu-148449DiVA, id: diva2:1216298
Subject / course
Computer Programming
Presentation
2018-06-08, I204, Campus Valla, Linköping, 08:15 (Swedish)
Supervisors
Examiners
Available from: 2018-06-28 Created: 2018-06-11 Last updated: 2018-06-28Bibliographically approved

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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
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf