DocumentCode :
3580883
Title :
Automatic fetal organs detection and approximation in ultrasound image using boosting classifier and hough transform
Author :
Ma´sum, M. Anwar ; Jatmiko, Wisnu ; Tawakal, M. Iqbal ; Al Afif, Faris
Author_Institution :
Fac. of Comput. Sci., Univ. Indonesia, Depok, Indonesia
fYear :
2014
Firstpage :
460
Lastpage :
467
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.
Keywords :
Hough transforms; biological organs; biomedical ultrasonics; image classification; medical image processing; Adaboost.MH; automatic fetal organ approximation; automatic fetal organ detection; boosting classifier; fetal abdomen; fetal femur; fetal head; fetal humerus; hamming error; mean kappa coefficient; multistump classifier; randomized Hough transform; ultrasound image; Approximation methods; Biological systems; Equations; Image segmentation; Mathematical model; Transforms; Ultrasonic imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Science and Information Systems (ICACSIS), 2014 International Conference on
Type :
conf
DOI :
10.1109/ICACSIS.2014.7065897
Filename :
7065897
Link To Document :
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