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Author Notes:

Corresponding author. Tel.: +1 404 894 6609; fax: +1 404 894 0673. andrzej@cc.gatech.edu (A. Szymczak). aestillman@earthlink.net (A. Stillman), tannenba@ece.gatech.edu (A. Tannenbaum), mischaik@math.gatech.edu (K. Mischaikow).


Research Funding:

This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149.

This work was also supported by a Grant from NIH (NAC P41 RR-13218) through Brigham and Women’s Hospital and NSF Grants DMS-0138420 and DMS-0107396.


  • Science & Technology
  • Technology
  • Life Sciences & Biomedicine
  • Computer Science, Artificial Intelligence
  • Computer Science, Interdisciplinary Applications
  • Engineering, Biomedical
  • Radiology, Nuclear Medicine & Medical Imaging
  • Computer Science
  • Engineering
  • persistence
  • minimum spanning tree
  • vessel tree reconstruction

Coronary vessel trees from 3D imagery: A topological approach


Journal Title:

Medical Image Analysis


Volume 10, Number 4


, Pages 548-559

Type of Work:

Article | Post-print: After Peer Review


We propose a simple method for reconstructing vascular trees from 3D images. Our algorithm extracts persistent maxima of the intensity on all axis-aligned 2D slices of the input image. The maxima concentrate along 1D intensity ridges, in particular along blood vessels. We build a forest connecting the persistent maxima with short edges. The forest tends to approximate the blood vessels present in the image, but also contains numerous spurious features and often fails to connect segments belonging to one vessel in low contrast areas. We improve the forest by applying simple geometric filters that trim short branches, fill gaps in blood vessels and remove spurious branches from the vascular tree to be extracted. Experiments show that our technique can be applied to extract coronary trees from heart CT scans.

Copyright information:

© 2006 Elsevier B.V. All rights reserved.

This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Creative Commons License

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