NDLI: Surface Extraction Using SVM-Based Texture Classification for 3D Fetal Ultrasound Imaging

Content Provider	IEEE Xplore Digital Library
Author	Tien Dung Nguyen Sang Hyun Kim Nam Chul Kim
Copyright Year	2006
Description	Author affiliation: Fac. of Electron. & Telecommun., Hanoi Univ. of Technol., Vietnam (Tien Dung Nguyen)
Abstract	This paper presents a new method for extracting the frontal surface of a fetus automatically from a three-dimensional (3D) fetal ultrasound volume using support vector machine (SVM) based texture classification. Since a fetus often floats on amniotic fluids in its mother's uterus, the major part of the frontal surface may be extracted removing dark regions corresponding to the amniotic fluid regions. In this method, the removal of dark regions in a VOI of the volume is performed by a Laplacian-of-Gaussian (LoG) followed by zero-crossing detection, which is called coarse segmentation. In the regions segmented coarsely, some are fetus regions, some non-fetus regions such as the uterus, abdomen, and floating matters, and other mixed ones of the two. In order to extract more pure fetus regions, fine segmentation is executed to split the regions into more homogeneous sub-regions. The textureness of each sub-region is then measured by multi-window BDIP and multi-window BVLC moments and classified into fetus and non-fetus ones by a SVM which is known as efficient classification tool. The frontal contours extracted from merging adjacent fetus sub-regions is combined in all the frames of the VOI to generate a fetal surface, which defines a mask volume for 3D visualization of the fetus. Experimental results show that the proposed method is useful for automatic visualization of a fetus without intervention of a user in 3D ultrasound imaging.
Starting Page	285
Ending Page	290
File Size	7942215
Page Count	6
File Format	PDF
ISBN	1424405688
DOI	10.1109/CCE.2006.350830
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-10-10
Publisher Place	Vietnam
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape fetal surface Data mining Support vector machines Image segmentation Ultrasonic imaging support vector machine Amniotic fluid Data visualization Support vector machine classification Fetus segmentation ultrasound image Surface texture texture classification
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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