Reconstruction and error detection of blood vessel network from ultrasound volume data

Kohji Masuda, Antoine Bossard, Yuki Sugano, Toshikazu Kato, Shinya Onogi

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Recently, we described a reconstruction method of the blood vessel network by 3D thinning to detect vessels bifurcations, which is applied to the control of microbubbles in vivo. However, that method did not include error detections and was only verified on a very simply shaped artificial blood vessel. In this paper we propose a system including an abstraction method for the blood vessel network. Such a model is then analyzed through graph theory and error patterns in the reconstructed network. We proceeded in vitro by acquiring volume data from an artificial capillary with multi-bifurcations whose diameter ranges from 0.5 to 2.0mm and with different flow velocities. We were able to reconstruct the blood vessel network of an in vitro artificial capillary with multi-bifurcations. Results show that our system successfully reconstructed the corresponding networks as much as the limitation of resolution of echography.

Original languageEnglish
Article number6627850
Pages (from-to)497-501
Number of pages5
JournalProceedings - IEEE Symposium on Computer-Based Medical Systems
Publication statusPublished - 2013
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications


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