Deep learning and particle filter-based aortic dissection vessel tree segmentation

Yuan Jin*, Antonio Pepe, Jianning Li, Christina Gsaxner, Jan Egger

*Corresponding author for this work

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

Abstract

Aortic dissections (AD) are injuries of the inner vessel wall of the (human) aorta. As this disease poses a significant threat to a patient's life, it is crucial to observe and analyze the progression of the dissection over the course of the disease. The clinical examinations are usually performed with the application of Computed Tomography (CT) or Computed Tomography Angiography (CTA), based on which, automated post-processing procedures would be beneficial for the management of critical pathologies. One of the main tasks during post-processing is aorta segmentation. Different methods have been developed for the segmentation of aorta, including the tracking methods, the active contour/surface methods and the deep learning methods. In this study, a method for the automatic segmentation of aorta and its branches from original thorax CT and CTA images is introduced. The aorta is segmented based on deep learning algorithm and afterwards the branches are tracked based on particle filter algorithm.

Original languageEnglish
Title of host publicationMedical Imaging 2021
Subtitle of host publicationBiomedical Applications in Molecular, Structural, and Functional Imaging
EditorsBarjor S. Gimi, Andrzej Krol
PublisherSPIE
ISBN (Electronic)9781510640290
DOIs
Publication statusPublished - 2021
EventMedical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging - Virtual, Online, United States
Duration: 15 Feb 202119 Feb 2021

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume11600
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging
Country/TerritoryUnited States
CityVirtual, Online
Period15/02/2119/02/21

Keywords

  • Aortic Dissection
  • Computed Tomography Angiography
  • Deep Learning
  • Particle Filter.
  • Segmentation
  • V-Net

ASJC Scopus subject areas

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

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