Geometric modeling of aortic dissections through convolution surfaces

Luana Petrelli, Antonio Pepe*, Antonella Disanto, Christina Gsaxner, Jianning Li, Yuan Jin, Domenico Buongiorno, Antonio Brunetti, Vitoantonio Bevilacqua, Jan Egger

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


Cardiovascular diseases are one of the strongest burdens in healthcare. If misdiagnosed, they can lead to life-threatening complications. This is especially true for aortic dissections, which may require immediate surgery depending on the categorization and still lead to late adverse events. Aortic dissection occurs when the aortic duct splits into two blood streams, the true and false lumina. The morphological characteristics of the aorta are therefore crucial for a clinician and provide vital support since they can be used to extract significant information for surgery and treatment planning. In this work, we revive a successful modeling technique - convolution surfaces - to model the lumina in aortic dissections. The skeleton of the lumina and local radial information are used to represent the true and the false lumen through convolution of local segments. Additionally, we introduce an optimization strategy based on a genetic algorithm to create the separation caused by the dissection flap.

Original languageEnglish
Title of host publicationMedical Imaging 2022
Subtitle of host publicationImaging Informatics for Healthcare, Research, and Applications
EditorsThomas M. Deserno, Thomas M. Deserno, Brian J. Park
ISBN (Electronic)9781510649491
Publication statusPublished - 2022
EventMedical Imaging 2022: Imaging Informatics for Healthcare, Research, and Applications - Virtual, Online
Duration: 21 Mar 202227 Mar 2022

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (Print)1605-7422


ConferenceMedical Imaging 2022: Imaging Informatics for Healthcare, Research, and Applications
CityVirtual, Online


  • CTA
  • genetic algorithm
  • implicit modeling
  • vessel reconstruction

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Biomaterials
  • Radiology Nuclear Medicine and imaging


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