Automatic fetal organs detection and approximation in ultrasound image using boosting classifier and hough transform

M. Anwar Ma'Sum, Wisnu Jatmiko, M. Iqbal Tawakal, Faris Al Afif

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - ICACSIS 2014
Subtitle of host publication2014 International Conference on Advanced Computer Science and Information Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages460-467
Number of pages8
ISBN (Electronic)9781479980758
DOIs
Publication statusPublished - 23 Mar 2014
Event2014 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2014 - Jakarta, Indonesia
Duration: 18 Oct 201419 Oct 2014

Publication series

NameProceedings - ICACSIS 2014: 2014 International Conference on Advanced Computer Science and Information Systems

Conference

Conference2014 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2014
Country/TerritoryIndonesia
CityJakarta
Period18/10/1419/10/14

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