Abstract: Estimation of the Principal Ischaemic Stroke Growth Directions for Predicting Tissue Outcomes

Christian Lucas; Linda F. Aulmann; André Kemmling; Amir Madany Mamlouk; Mattias P. Heinrich

doi:10.1007/978-3-658-29267-6_29

Abstract: Estimation of the Principal Ischaemic Stroke Growth Directions for Predicting Tissue Outcomes

Christian Lucas^*, Linda F. Aulmann, André Kemmling, Amir Madany Mamlouk, Mattias P. Heinrich

^*Korrespondierende/r Autor/-in für diese Arbeit

Abstract

The estimates of traditional segmentation CNNs for the prediction of the follow-up tissue outcome in strokes are not yet accurate enough or capable of properly modeling the growth mechanisms of ischaemic stroke [1]. In our previous shape space interpolation approach [2], the prediction of the follow-up lesion shape has been bounded using core and penumbra segmentation estimates as priors. One of the challenges is to define well-suited growth constraints, as the transition from one to another shape may still result in a very unrealistic spatial evolution of the stroke.

Originalsprache	Englisch
Titel	Bildverarbeitung für die Medizin 2020
Redakteure/-innen	Thomas Tolxdorff, Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Christoph Palm
Seitenumfang	1
Erscheinungsort	Wiesbaden
Herausgeber (Verlag)	Springer Vieweg, Wiesbaden
Erscheinungsdatum	12.02.2020
Seiten	143-143
ISBN (Print)	978-3-658-29266-9
ISBN (elektronisch)	978-3-658-29267-6
DOIs	https://doi.org/10.1007/978-3-658-29267-6_29
Publikationsstatus	Veröffentlicht - 12.02.2020
Veranstaltung	Bildverarbeitung für die Medizin 2020 - International workshop on Algorithmen - Systeme - Anwendungen - Berlin, Deutschland Dauer: 15.03.2020 → 17.03.2020 Konferenznummer: 237969

Strategische Forschungsbereiche und Zentren

Zentren: Zentrum für Künstliche Intelligenz Lübeck (ZKIL)
Querschnittsbereich: Intelligente Systeme

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

Zugriff auf Dokument

10.1007/978-3-658-29267-6_29

Andere Dateien und Links

www.scopus.com

Zitieren

Lucas, C., Aulmann, L. F., Kemmling, A., Mamlouk, A. M., & Heinrich, M. P. (2020). Abstract: Estimation of the Principal Ischaemic Stroke Growth Directions for Predicting Tissue Outcomes. in T. Tolxdorff, T. M. Deserno, H. Handels, A. Maier, K. H. Maier-Hein, & C. Palm (Hrsg.), Bildverarbeitung für die Medizin 2020 (S. 143-143). (Informatik aktuell). Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-29267-6_29

Lucas, Christian ; Aulmann, Linda F. ; Kemmling, André et al. / Abstract: Estimation of the Principal Ischaemic Stroke Growth Directions for Predicting Tissue Outcomes. Bildverarbeitung für die Medizin 2020. Hrsg. / Thomas Tolxdorff ; Thomas M. Deserno ; Heinz Handels ; Andreas Maier ; Klaus H. Maier-Hein ; Christoph Palm. Wiesbaden : Springer Vieweg, Wiesbaden, 2020. S. 143-143 (Informatik aktuell).

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abstract = "The estimates of traditional segmentation CNNs for the prediction of the follow-up tissue outcome in strokes are not yet accurate enough or capable of properly modeling the growth mechanisms of ischaemic stroke [1]. In our previous shape space interpolation approach [2], the prediction of the follow-up lesion shape has been bounded using core and penumbra segmentation estimates as priors. One of the challenges is to define well-suited growth constraints, as the transition from one to another shape may still result in a very unrealistic spatial evolution of the stroke.",

author = "Christian Lucas and Aulmann, {Linda F.} and Andr{\'e} Kemmling and Mamlouk, {Amir Madany} and Heinrich, {Mattias P.}",

note = "Publisher Copyright: {\textcopyright} Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2020. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; Bildverarbeitung f{\"u}r die Medizin 2020 - International workshop on Algorithmen - Systeme - Anwendungen<br/> ; Conference date: 15-03-2020 Through 17-03-2020",

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doi = "10.1007/978-3-658-29267-6_29",

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Lucas, C, Aulmann, LF, Kemmling, A, Mamlouk, AM & Heinrich, MP 2020, Abstract: Estimation of the Principal Ischaemic Stroke Growth Directions for Predicting Tissue Outcomes. in T Tolxdorff, T M. Deserno, H Handels, A Maier, K H. Maier-Hein & C Palm (Hrsg.), Bildverarbeitung für die Medizin 2020. Informatik aktuell, Springer Vieweg, Wiesbaden, Wiesbaden, S. 143-143, Bildverarbeitung für die Medizin 2020 - International workshop on Algorithmen - Systeme - Anwendungen
, Berlin, Berlin, Deutschland, 15.03.20. https://doi.org/10.1007/978-3-658-29267-6_29

Abstract: Estimation of the Principal Ischaemic Stroke Growth Directions for Predicting Tissue Outcomes. / Lucas, Christian; Aulmann, Linda F.; Kemmling, André et al.
Bildverarbeitung für die Medizin 2020. Hrsg. / Thomas Tolxdorff; Thomas M. Deserno; Heinz Handels; Andreas Maier; Klaus H. Maier-Hein; Christoph Palm. Wiesbaden: Springer Vieweg, Wiesbaden, 2020. S. 143-143 (Informatik aktuell).

Publikation: Kapitel in Büchern/Berichten/Konferenzbänden › Konferenzbeitrag › Begutachtung

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T1 - Abstract: Estimation of the Principal Ischaemic Stroke Growth Directions for Predicting Tissue Outcomes

AU - Lucas, Christian

AU - Aulmann, Linda F.

AU - Kemmling, André

AU - Mamlouk, Amir Madany

AU - Heinrich, Mattias P.

N1 - Conference code: 237969

PY - 2020/2/12

Y1 - 2020/2/12

N2 - The estimates of traditional segmentation CNNs for the prediction of the follow-up tissue outcome in strokes are not yet accurate enough or capable of properly modeling the growth mechanisms of ischaemic stroke [1]. In our previous shape space interpolation approach [2], the prediction of the follow-up lesion shape has been bounded using core and penumbra segmentation estimates as priors. One of the challenges is to define well-suited growth constraints, as the transition from one to another shape may still result in a very unrealistic spatial evolution of the stroke.

AB - The estimates of traditional segmentation CNNs for the prediction of the follow-up tissue outcome in strokes are not yet accurate enough or capable of properly modeling the growth mechanisms of ischaemic stroke [1]. In our previous shape space interpolation approach [2], the prediction of the follow-up lesion shape has been bounded using core and penumbra segmentation estimates as priors. One of the challenges is to define well-suited growth constraints, as the transition from one to another shape may still result in a very unrealistic spatial evolution of the stroke.

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BT - Bildverarbeitung für die Medizin 2020

A2 - Tolxdorff, Thomas

A2 - M. Deserno, Thomas

A2 - Handels, Heinz

A2 - Maier, Andreas

A2 - H. Maier-Hein, Klaus

A2 - Palm, Christoph

PB - Springer Vieweg, Wiesbaden

CY - Wiesbaden

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Lucas C, Aulmann LF, Kemmling A, Mamlouk AM , Heinrich MP. Abstract: Estimation of the Principal Ischaemic Stroke Growth Directions for Predicting Tissue Outcomes. in Tolxdorff T, M. Deserno T, Handels H, Maier A, H. Maier-Hein K, Palm C, Hrsg., Bildverarbeitung für die Medizin 2020. Wiesbaden: Springer Vieweg, Wiesbaden. 2020. S. 143-143. (Informatik aktuell). doi: 10.1007/978-3-658-29267-6_29