Ventricular blood flow analysis using topological methods

Scott Kulp; Chao Chen; Dimitris Metaxas; Leon Axel

doi:10.1109/ISBI.2015.7163960

Ventricular blood flow analysis using topological methods

Scott Kulp
, Chao Chen
, Dimitris Metaxas
, Leon Axel

Biomedical Informatics

Rutgers - The State University of New Jersey, New Brunswick
New York University

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

Abstract

Thanks to the advances of data acquisition techniques, we can acquire ventricular blood flow data with very high quality. This extremely complex spatiotemporal data calls for novel visualization and analysis tools. In particular, the new tools need to assist domain experts in quick identification of critical patterns. In this paper, we present a method using topo-logical data analysis tools with simulated ventricular blood flow, and automatically detect interesting topological features within the flow. We show that this completely unsupervised framework detects and extracts eddies formed from vortex shedding during late diastole, which normally requires highly specialized algorithms to capture.

Original language	English
Title of host publication	2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015
Publisher	IEEE Computer Society
Pages	663-666
Number of pages	4
ISBN (Electronic)	9781479923748
DOIs	https://doi.org/10.1109/ISBI.2015.7163960
State	Published - Jul 21 2015
Event	12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 - Brooklyn, United States Duration: Apr 16 2015 → Apr 19 2015

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging
Volume	2015-July
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Conference

Conference	12th IEEE International Symposium on Biomedical Imaging, ISBI 2015
Country/Territory	United States
City	Brooklyn
Period	04/16/15 → 04/19/15

Keywords

persistent homology
spatiotemporal data
topological methods
Ventricular flow analysis

Access to Document

10.1109/ISBI.2015.7163960

Cite this

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title = "Ventricular blood flow analysis using topological methods",

abstract = "Thanks to the advances of data acquisition techniques, we can acquire ventricular blood flow data with very high quality. This extremely complex spatiotemporal data calls for novel visualization and analysis tools. In particular, the new tools need to assist domain experts in quick identification of critical patterns. In this paper, we present a method using topo-logical data analysis tools with simulated ventricular blood flow, and automatically detect interesting topological features within the flow. We show that this completely unsupervised framework detects and extracts eddies formed from vortex shedding during late diastole, which normally requires highly specialized algorithms to capture.",

keywords = "persistent homology, spatiotemporal data, topological methods, Ventricular flow analysis",

author = "Scott Kulp and Chao Chen and Dimitris Metaxas and Leon Axel",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 ; Conference date: 16-04-2015 Through 19-04-2015",

year = "2015",

month = jul,

day = "21",

doi = "10.1109/ISBI.2015.7163960",

language = "English",

series = "Proceedings - International Symposium on Biomedical Imaging",

publisher = "IEEE Computer Society",

pages = "663--666",

booktitle = "2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015",

}

Kulp, S, Chen, C, Metaxas, D & Axel, L 2015, Ventricular blood flow analysis using topological methods. in 2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015., 7163960, Proceedings - International Symposium on Biomedical Imaging, vol. 2015-July, IEEE Computer Society, pp. 663-666, 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015, Brooklyn, United States, 04/16/15. https://doi.org/10.1109/ISBI.2015.7163960

Ventricular blood flow analysis using topological methods. / Kulp, Scott; Chen, Chao; Metaxas, Dimitris et al.
2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015. IEEE Computer Society, 2015. p. 663-666 7163960 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2015-July).

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

TY - GEN

T1 - Ventricular blood flow analysis using topological methods

AU - Kulp, Scott

AU - Chen, Chao

AU - Metaxas, Dimitris

AU - Axel, Leon

PY - 2015/7/21

Y1 - 2015/7/21

N2 - Thanks to the advances of data acquisition techniques, we can acquire ventricular blood flow data with very high quality. This extremely complex spatiotemporal data calls for novel visualization and analysis tools. In particular, the new tools need to assist domain experts in quick identification of critical patterns. In this paper, we present a method using topo-logical data analysis tools with simulated ventricular blood flow, and automatically detect interesting topological features within the flow. We show that this completely unsupervised framework detects and extracts eddies formed from vortex shedding during late diastole, which normally requires highly specialized algorithms to capture.

AB - Thanks to the advances of data acquisition techniques, we can acquire ventricular blood flow data with very high quality. This extremely complex spatiotemporal data calls for novel visualization and analysis tools. In particular, the new tools need to assist domain experts in quick identification of critical patterns. In this paper, we present a method using topo-logical data analysis tools with simulated ventricular blood flow, and automatically detect interesting topological features within the flow. We show that this completely unsupervised framework detects and extracts eddies formed from vortex shedding during late diastole, which normally requires highly specialized algorithms to capture.

KW - persistent homology

KW - spatiotemporal data

KW - topological methods

KW - Ventricular flow analysis

UR - https://www.scopus.com/pages/publications/84944323922

U2 - 10.1109/ISBI.2015.7163960

DO - 10.1109/ISBI.2015.7163960

M3 - Conference contribution

AN - SCOPUS:84944323922

T3 - Proceedings - International Symposium on Biomedical Imaging

SP - 663

EP - 666

BT - 2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015

PB - IEEE Computer Society

T2 - 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015

Y2 - 16 April 2015 through 19 April 2015

ER -

Ventricular blood flow analysis using topological methods

Abstract

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Conference

Keywords

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