DocumentCode
3544538
Title
Foetus Ultrasound Medical Image Segmentation via Variational Level Set Algorithm
Author
Choong, M.Y. ; Seng, M.C. ; Yang, S.S. ; Kiring, A. ; Teo, K.T.K.
Author_Institution
Modelling, Simulation & Comput. Lab., Univ. Malaysia Sabah, Kota Kinabalu, Malaysia
fYear
2012
fDate
8-10 Feb. 2012
Firstpage
225
Lastpage
229
Abstract
There is a challenge to segment the medical image which is often blurred and consists of noise. The objects to be segmented are always changing shape. Thus, there is a need to apply a method to automated segment well the objects for future analysis without any assumptions about the object´s topology are made. In general, when performing pregnancy ultrasound scanning, obstetrician needs to find out the best position or angle of the foetus and freeze the scene. The obstetrician will click on the crown and the rump of the foetus to get the foetus length. The segmentation technique applied is level set method. A variational level set algorithm has been successfully implemented in medical image segmentation (Xray image, MRI image and ultrasound image). The results showed the level set contour evolved well on the low contrast and noise consisting medical image, especially the ultrasound image.
Keywords
biomedical ultrasonics; image segmentation; medical image processing; obstetrics; shape recognition; topology; automated segmentation; foetus angle; foetus length; foetus ultrasound medical image segmentation; object topology; obstetrician; pregnancy ultrasound scanning; shape changes; variational level set algorithm; Biomedical imaging; Image segmentation; Level set; Magnetic resonance imaging; Shape; Ultrasonic imaging; Ultrasonic variables measurement; foetus ultrasound medical image; image segmentation; level set algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems, Modelling and Simulation (ISMS), 2012 Third International Conference on
Conference_Location
Kota Kinabalu
Print_ISBN
978-1-4673-0886-1
Type
conf
DOI
10.1109/ISMS.2012.102
Filename
6169704
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