Automated IVUS contour detection using intensity features and Radial Basis Function approximation

Maria Papadogiorgaki; Vasileios Mezaris; Yiannis S. Chatzizisis; George D. Giannoglou; Ioannis Kompatsiaris

doi:10.1109/CBMS.2007.27

Automated IVUS contour detection using intensity features and Radial Basis Function approximation

Maria Papadogiorgaki, Vasileios Mezaris, Yiannis S. Chatzizisis, George D. Giannoglou, Ioannis Kompatsiaris

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

9 Scopus citations

Abstract

Intravascular ultrasound (IVUS) constitutes a valuable technique for the diagnosis and management of coronary atherosclerosis. The detection of lumen and media-adventitia borders in IVUS images represents a necessary step in the utilization of the IVUS data for the reliable quantitative assessment of atherosclerotic lesions. In this paper, a fully automated technique for the detection of lumen and media-adventitia boundaries is developed. This comprises two different steps for contour initialization, one for each corresponding contour of interest, and a procedure for the refinement of the detected contours based on Radial Basis Function approximation. The proposed approach is shown to be capable of performing quick and reliable automated segmentation of IVUS images.

Original language	English (US)
Title of host publication	Proceedings - Twentieth IEEE International Symposium on Computer-Based Medical Systems, CBMS'07
Pages	183-188
Number of pages	6
DOIs	https://doi.org/10.1109/CBMS.2007.27
State	Published - 2007
Externally published	Yes
Event	20th IEEE International Symposium on Computer-Based Medical Systems, CBMS'07 - Maribor, Slovenia Duration: Jun 20 2007 → Jun 22 2007

Publication series

Name	Proceedings - IEEE Symposium on Computer-Based Medical Systems
ISSN (Print)	1063-7125

Conference

Conference	20th IEEE International Symposium on Computer-Based Medical Systems, CBMS'07
Country/Territory	Slovenia
City	Maribor
Period	6/20/07 → 6/22/07

ASJC Scopus subject areas

Radiology Nuclear Medicine and imaging
Computer Science Applications

Access to Document

10.1109/CBMS.2007.27

Cite this

Papadogiorgaki, M., Mezaris, V., Chatzizisis, Y. S., Giannoglou, G. D., & Kompatsiaris, I. (2007). Automated IVUS contour detection using intensity features and Radial Basis Function approximation. In Proceedings - Twentieth IEEE International Symposium on Computer-Based Medical Systems, CBMS'07 (pp. 183-188). Article 4262647 (Proceedings - IEEE Symposium on Computer-Based Medical Systems). https://doi.org/10.1109/CBMS.2007.27

Automated IVUS contour detection using intensity features and Radial Basis Function approximation. / Papadogiorgaki, Maria; Mezaris, Vasileios; Chatzizisis, Yiannis S. et al.
Proceedings - Twentieth IEEE International Symposium on Computer-Based Medical Systems, CBMS'07. 2007. p. 183-188 4262647 (Proceedings - IEEE Symposium on Computer-Based Medical Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Papadogiorgaki, M, Mezaris, V, Chatzizisis, YS, Giannoglou, GD & Kompatsiaris, I 2007, Automated IVUS contour detection using intensity features and Radial Basis Function approximation. in Proceedings - Twentieth IEEE International Symposium on Computer-Based Medical Systems, CBMS'07., 4262647, Proceedings - IEEE Symposium on Computer-Based Medical Systems, pp. 183-188, 20th IEEE International Symposium on Computer-Based Medical Systems, CBMS'07, Maribor, Slovenia, 6/20/07. https://doi.org/10.1109/CBMS.2007.27

Papadogiorgaki M, Mezaris V, Chatzizisis YS, Giannoglou GD, Kompatsiaris I. Automated IVUS contour detection using intensity features and Radial Basis Function approximation. In Proceedings - Twentieth IEEE International Symposium on Computer-Based Medical Systems, CBMS'07. 2007. p. 183-188. 4262647. (Proceedings - IEEE Symposium on Computer-Based Medical Systems). doi: 10.1109/CBMS.2007.27

@inproceedings{ee0a404fae5a4363bb73a15bfdf0ae56,

title = "Automated IVUS contour detection using intensity features and Radial Basis Function approximation",

abstract = "Intravascular ultrasound (IVUS) constitutes a valuable technique for the diagnosis and management of coronary atherosclerosis. The detection of lumen and media-adventitia borders in IVUS images represents a necessary step in the utilization of the IVUS data for the reliable quantitative assessment of atherosclerotic lesions. In this paper, a fully automated technique for the detection of lumen and media-adventitia boundaries is developed. This comprises two different steps for contour initialization, one for each corresponding contour of interest, and a procedure for the refinement of the detected contours based on Radial Basis Function approximation. The proposed approach is shown to be capable of performing quick and reliable automated segmentation of IVUS images.",

author = "Maria Papadogiorgaki and Vasileios Mezaris and Chatzizisis, {Yiannis S.} and Giannoglou, {George D.} and Ioannis Kompatsiaris",

year = "2007",

doi = "10.1109/CBMS.2007.27",

language = "English (US)",

isbn = "0769529054",

series = "Proceedings - IEEE Symposium on Computer-Based Medical Systems",

pages = "183--188",

booktitle = "Proceedings - Twentieth IEEE International Symposium on Computer-Based Medical Systems, CBMS'07",

note = "20th IEEE International Symposium on Computer-Based Medical Systems, CBMS'07 ; Conference date: 20-06-2007 Through 22-06-2007",

}

TY - GEN

T1 - Automated IVUS contour detection using intensity features and Radial Basis Function approximation

AU - Papadogiorgaki, Maria

AU - Mezaris, Vasileios

AU - Chatzizisis, Yiannis S.

AU - Giannoglou, George D.

AU - Kompatsiaris, Ioannis

PY - 2007

Y1 - 2007

N2 - Intravascular ultrasound (IVUS) constitutes a valuable technique for the diagnosis and management of coronary atherosclerosis. The detection of lumen and media-adventitia borders in IVUS images represents a necessary step in the utilization of the IVUS data for the reliable quantitative assessment of atherosclerotic lesions. In this paper, a fully automated technique for the detection of lumen and media-adventitia boundaries is developed. This comprises two different steps for contour initialization, one for each corresponding contour of interest, and a procedure for the refinement of the detected contours based on Radial Basis Function approximation. The proposed approach is shown to be capable of performing quick and reliable automated segmentation of IVUS images.

AB - Intravascular ultrasound (IVUS) constitutes a valuable technique for the diagnosis and management of coronary atherosclerosis. The detection of lumen and media-adventitia borders in IVUS images represents a necessary step in the utilization of the IVUS data for the reliable quantitative assessment of atherosclerotic lesions. In this paper, a fully automated technique for the detection of lumen and media-adventitia boundaries is developed. This comprises two different steps for contour initialization, one for each corresponding contour of interest, and a procedure for the refinement of the detected contours based on Radial Basis Function approximation. The proposed approach is shown to be capable of performing quick and reliable automated segmentation of IVUS images.

UR - http://www.scopus.com/inward/record.url?scp=34748905877&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34748905877&partnerID=8YFLogxK

U2 - 10.1109/CBMS.2007.27

DO - 10.1109/CBMS.2007.27

M3 - Conference contribution

AN - SCOPUS:34748905877

SN - 0769529054

SN - 9780769529059

T3 - Proceedings - IEEE Symposium on Computer-Based Medical Systems

SP - 183

EP - 188

BT - Proceedings - Twentieth IEEE International Symposium on Computer-Based Medical Systems, CBMS'07

T2 - 20th IEEE International Symposium on Computer-Based Medical Systems, CBMS'07

Y2 - 20 June 2007 through 22 June 2007

ER -

Automated IVUS contour detection using intensity features and Radial Basis Function approximation

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this