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

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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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title = "Abstract: Estimation of the Principal Ischaemic Stroke Growth Directions for Predicting Tissue Outcomes",

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",

year = "2020",

month = feb,

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

language = "English",

isbn = "978-3-658-29266-9",

series = "Informatik aktuell",

publisher = "Springer Vieweg, Wiesbaden",

pages = "143--143",

editor = "Tolxdorff, \{Thomas \} and \{M. Deserno\}, \{Thomas \} and Handels, \{Heinz \} and Maier, \{Andreas \} and \{H. Maier-Hein\}, \{Klaus \} and Palm, \{Christoph \}",

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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

TY - GEN

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.

UR - https://www.scopus.com/pages/publications/85083081868

U2 - 10.1007/978-3-658-29267-6_29

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

M3 - Conference contribution

SN - 978-3-658-29266-9

T3 - Informatik aktuell

SP - 143

EP - 143

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

T2 - Bildverarbeitung für die Medizin 2020 - International workshop on Algorithmen - Systeme - Anwendungen<br/>

Y2 - 15 March 2020 through 17 March 2020

ER -

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

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

Abstract

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