A study of AAA image segmentation technique using geometric active contour model with morphological gradient edge function

H. C. Kim, Y. H. Seol, S. Y. Choi, J. S. Oh, M. G. Kim, Kyung Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Abdominal aortic aneurysm (AAA) is a serious vascular disease that can be life threatening. Accurate measurement of AAA size is important for surgical or endovascular repair. We have examined the feasibility of using the proposed method to drive quantitative measurement of a region of interest from AAA. The proposed geometric active contour model (PGACM) is a modification of the conventional geometric active contour model (CGACM) that uses morphological gradient edge function rather than Gaussian filtered images. The rationale for this is to eliminate the blurring effect induced by the Gaussian filter in the CGACM. We used three noised synthetic images with different shapes. To test performance, three quantities that were normalized for minimum distance error, mismatched area, and execution time are evaluated. PGACM, parametric active contour model (PACM), and CGACM were compared with respect to the three quantities. With PGACM, we obtained better performance for the segmentation than with the PACM and CGACM. This study shows the feasibility, accuracy, and precision of segmentation of AAA from CT data, and indicates that the proposed method may be useful in patients with AAA.

Original languageEnglish
Title of host publication29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
Pages4437-4440
Number of pages4
DOIs
Publication statusPublished - 2007 Dec 1
Event29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 - Lyon, France
Duration: 2007 Aug 232007 Aug 26

Other

Other29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
CountryFrance
CityLyon
Period07/8/2307/8/26

Fingerprint

Abdominal Aortic Aneurysm
Image segmentation
Feasibility Studies
Vascular Diseases
Repair

Keywords

  • Geometric active contour model
  • Morphological gradient edge function

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Kim, H. C., Seol, Y. H., Choi, S. Y., Oh, J. S., Kim, M. G., & Sun, K. (2007). A study of AAA image segmentation technique using geometric active contour model with morphological gradient edge function. In 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 (pp. 4437-4440). [4353323] https://doi.org/10.1109/IEMBS.2007.4353323

A study of AAA image segmentation technique using geometric active contour model with morphological gradient edge function. / Kim, H. C.; Seol, Y. H.; Choi, S. Y.; Oh, J. S.; Kim, M. G.; Sun, Kyung.

29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07. 2007. p. 4437-4440 4353323.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kim, HC, Seol, YH, Choi, SY, Oh, JS, Kim, MG & Sun, K 2007, A study of AAA image segmentation technique using geometric active contour model with morphological gradient edge function. in 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07., 4353323, pp. 4437-4440, 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07, Lyon, France, 07/8/23. https://doi.org/10.1109/IEMBS.2007.4353323
Kim HC, Seol YH, Choi SY, Oh JS, Kim MG, Sun K. A study of AAA image segmentation technique using geometric active contour model with morphological gradient edge function. In 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07. 2007. p. 4437-4440. 4353323 https://doi.org/10.1109/IEMBS.2007.4353323
Kim, H. C. ; Seol, Y. H. ; Choi, S. Y. ; Oh, J. S. ; Kim, M. G. ; Sun, Kyung. / A study of AAA image segmentation technique using geometric active contour model with morphological gradient edge function. 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07. 2007. pp. 4437-4440
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