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

^*Corresponding author for this work

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.

Original language	English
Title of host publication	Bildverarbeitung für die Medizin 2020
Editors	Thomas Tolxdorff, Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Christoph Palm
Number of pages	1
Place of Publication	Wiesbaden
Publisher	Springer Vieweg, Wiesbaden
Publication date	12.02.2020
Pages	143-143
ISBN (Print)	978-3-658-29266-9
ISBN (Electronic)	978-3-658-29267-6
DOIs	https://doi.org/10.1007/978-3-658-29267-6_29
Publication status	Published - 12.02.2020
Event	Bildverarbeitung für die Medizin 2020 - International workshop on Algorithmen - Systeme - Anwendungen - Berlin, Germany Duration: 15.03.2020 → 17.03.2020 Conference number: 237969

Research Areas and Centers

Centers: Center for Artificial Intelligence Luebeck (ZKIL)
Research Area: Intelligent Systems

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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

Cite this

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 (Eds.), Bildverarbeitung für die Medizin 2020 (pp. 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. editor / Thomas Tolxdorff ; Thomas M. Deserno ; Heinz Handels ; Andreas Maier ; Klaus H. Maier-Hein ; Christoph Palm. Wiesbaden : Springer Vieweg, Wiesbaden, 2020. pp. 143-143 (Informatik aktuell).

@inproceedings{88af80436f1c4c0891ca3084c4552f4d,

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",

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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 (eds), Bildverarbeitung für die Medizin 2020. Informatik aktuell, Springer Vieweg, Wiesbaden, Wiesbaden, pp. 143-143, Bildverarbeitung für die Medizin 2020 - International workshop on Algorithmen - Systeme - Anwendungen
, Berlin, Berlin, Germany, 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. ed. / Thomas Tolxdorff; Thomas M. Deserno; Heinz Handels; Andreas Maier; Klaus H. Maier-Hein; Christoph Palm. Wiesbaden: Springer Vieweg, Wiesbaden, 2020. p. 143-143 (Informatik aktuell).

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

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.

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

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

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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, editors, Bildverarbeitung für die Medizin 2020. Wiesbaden: Springer Vieweg, Wiesbaden. 2020. p. 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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