Deep learning based image registration in dynamic cardiac CT using a recursive cascade network approach

Karen Andrea Lara Hernandez; Ivan Juárez; Michaelle Pérez; Theresa Margarethe Rienmüller; Christian Baumgartner

doi:10.3217/978-3-85125-826-4-18

Deep learning based image registration in dynamic cardiac CT using a recursive cascade network approach

Karen Andrea Lara Hernandez, Ivan Juárez, Michaelle Pérez, Theresa Margarethe Rienmüller, Christian Baumgartner

Institut für Health Care Engineering mit Europaprüfstelle für Medizinprodukte (7180)

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Abstract

This paper presents the development of a
system theory-based model of the COVID-19 pan-
demic spread based on weekly reports available on
the EU Open Data Portal (EUODP). The considered
mathematical model will be represented in the S com-
plex domain as a transfer matrix. System identification
methodology, well known in control system theory,
was applied. Stability analysis with possibilities of con-
trollability and observability was considered. The
spread of a pandemic can be controlled by propor-
tional (P) action in an open loop.

Originalsprache	englisch
Titel	Proceedings Annual Meeting of the Austrian Society for Biomedical Engineering 2021
Untertitel	ÖGBMT 2021
Redakteure/-innen	Gernot Müller-Putz, Christian Baumgartner
Erscheinungsort	Graz
Herausgeber (Verlag)	Verlag der Technischen Universität Graz
Seiten	67-70
Seitenumfang	4
ISBN (elektronisch)	978-3-85125-826-4
DOIs	https://doi.org/10.3217/978-3-85125-826-4-18
Publikationsstatus	Veröffentlicht - 30 Sept. 2021
Veranstaltung	ÖGBMT Jahrestagung 2021: ÖGBMT 2021 - Graz University of Technology, Graz, Österreich Dauer: 30 Sept. 2021 → 1 Okt. 2021 https://oegbmt2021.tugraz.at/

Konferenz

Konferenz	ÖGBMT Jahrestagung 2021
Kurztitel	ÖGBMT 2021
Land/Gebiet	Österreich
Ort	Graz
Zeitraum	30/09/21 → 1/10/21
Internetadresse	https://oegbmt2021.tugraz.at/

Fields of Expertise

Human- & Biotechnology

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10.3217/978-3-85125-826-4-18Lizenz: CC BY 4.0

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Lara Hernandez, K. A., Juárez, I., Pérez, M., Rienmüller, T. M., & Baumgartner, C. (2021). Deep learning based image registration in dynamic cardiac CT using a recursive cascade network approach. in G. Müller-Putz, & C. Baumgartner (Hrsg.), Proceedings Annual Meeting of the Austrian Society for Biomedical Engineering 2021: ÖGBMT 2021 (S. 67-70). Verlag der Technischen Universität Graz. https://doi.org/10.3217/978-3-85125-826-4-18

Deep learning based image registration in dynamic cardiac CT using a recursive cascade network approach. / Lara Hernandez, Karen Andrea; Juárez, Ivan; Pérez, Michaelle et al.
Proceedings Annual Meeting of the Austrian Society for Biomedical Engineering 2021: ÖGBMT 2021. Hrsg. / Gernot Müller-Putz; Christian Baumgartner. Graz: Verlag der Technischen Universität Graz, 2021. S. 67-70.

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Lara Hernandez, KA, Juárez, I, Pérez, M, Rienmüller, TM & Baumgartner, C 2021, Deep learning based image registration in dynamic cardiac CT using a recursive cascade network approach. in G Müller-Putz & C Baumgartner (Hrsg.), Proceedings Annual Meeting of the Austrian Society for Biomedical Engineering 2021: ÖGBMT 2021. Verlag der Technischen Universität Graz, Graz, S. 67-70, ÖGBMT Jahrestagung 2021, Graz, Österreich, 30/09/21. https://doi.org/10.3217/978-3-85125-826-4-18

Lara Hernandez KA, Juárez I, Pérez M, Rienmüller TM , Baumgartner C. Deep learning based image registration in dynamic cardiac CT using a recursive cascade network approach. in Müller-Putz G, Baumgartner C, Hrsg., Proceedings Annual Meeting of the Austrian Society for Biomedical Engineering 2021: ÖGBMT 2021. Graz: Verlag der Technischen Universität Graz. 2021. S. 67-70 doi: 10.3217/978-3-85125-826-4-18

Lara Hernandez, Karen Andrea ; Juárez, Ivan ; Pérez, Michaelle et al. / Deep learning based image registration in dynamic cardiac CT using a recursive cascade network approach. Proceedings Annual Meeting of the Austrian Society for Biomedical Engineering 2021: ÖGBMT 2021. Hrsg. / Gernot Müller-Putz ; Christian Baumgartner. Graz : Verlag der Technischen Universität Graz, 2021. S. 67-70

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abstract = "This paper presents the development of a system theory-based model of the COVID-19 pan-demic spread based on weekly reports available on the EU Open Data Portal (EUODP). The considered mathematical model will be represented in the S com-plex domain as a transfer matrix. System identification methodology, well known in control system theory, was applied. Stability analysis with possibilities of con-trollability and observability was considered. The spread of a pandemic can be controlled by propor-tional (P) action in an open loop. ",

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Deep learning based image registration in dynamic cardiac CT using a recursive cascade network approach

Abstract

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