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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 languageEnglish
Title of host publicationBildverarbeitung für die Medizin 2020
EditorsThomas Tolxdorff, Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Christoph Palm
Number of pages1
Place of PublicationWiesbaden
PublisherSpringer Vieweg, Wiesbaden
Publication date12.02.2020
Pages143-143
ISBN (Print)978-3-658-29266-9
ISBN (Electronic)978-3-658-29267-6
DOIs
Publication statusPublished - 12.02.2020
EventBildverarbeitung für die Medizin 2020 - International workshop on Algorithmen - Systeme - Anwendungen
- Berlin, Germany
Duration: 15.03.202017.03.2020
Conference number: 237969

UN SDGs

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

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 4 - Quality Education
    SDG 4 Quality Education
  3. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  4. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities
  5. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  6. SDG 14 - Life Below Water
    SDG 14 Life Below Water
  7. SDG 15 - Life on Land
    SDG 15 Life on Land

Research Areas and Centers

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

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