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Automatic fetal organs detection and approximation in ultrasound image using boosting classifier and hough transform
KTH, School of Computer Science and Communication (CSC). Universitas Indonesia, Indonesia.
2014 (English)In: Proceedings - ICACSIS 2014: 2014 International Conference on Advanced Computer Science and Information Systems, 2014, 460-467 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we proposed a system for automatic fetal detection and approximation in ultrasound image. We used Adaboost. MH based on Multi Stump Classifier to detect fetal organs in ultrasound. After fetal organ detected, it is approximated using Randomized Hough Transform. Experiments result show that mean accuracy of the fetal organs detection reaches 93.92% with mean kappa coefficient value reaches 0.854 and mean hamming error reaches 0.032. Proposed method has better performance compared to other five methods proposed in previous researches. Fetal Organ shape approximation performance reaches 81% for fetal head, 57% for fetal abdomen, 72% of fetal femur, and 66% of fetal humérus.

Place, publisher, year, edition, pages
2014. 460-467 p.
Keyword [en]
Adaptive boosting, Feature extraction, Hough transforms, Image classification, Better performance, Boosting classifiers, Fetal head, Fetal organs, Kappa coefficient, Randomized Hough transform, Shape approximation, Ultrasound images, Ultrasonic applications
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-168858DOI: 10.1109/ICACSIS.2014.7065897Scopus ID: 2-s2.0-84946689594ISBN: 9781479980758 (print)OAI: oai:DiVA.org:kth-168858DiVA: diva2:819961
Conference
2014 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2014, 18 October 2014 through 19 October 2014
Note

QC 20150611

Available from: 2015-06-11 Created: 2015-06-09 Last updated: 2015-06-11Bibliographically approved

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Tawakal, Muhammad Iqbal
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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