Quantitative analysis of vascular structures using image processing

Yi Chun Lin, Pei Ju Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Vascularization, the growth of new blood vessels form the existing vessels, implies many pathological processes and needs to be reasonably quantified. However, most vascular analysis is done manually. This is a tedious and laborious work without consistence. In this paper, we will demonstrate the feasibility of automatic quantification of vascular structures by image processing. To quantify the formation of blood vessels, the following parameters are measured automatically from the processed images: total length of tubes, total number of loops, total tube area, total confluent areas, the number of confluent area and the number of nodal structures. In addition, the obtained number of loops and tube length are compared with the values measured manually. The experimental results show that the highest Hit Rate is 90.3% and the highest False Alarm Rate is 6.675%.

Original languageEnglish
Title of host publicationProceedings - 2012 4th International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2012
Pages278-283
Number of pages6
DOIs
Publication statusPublished - 2012 Oct 17
Event2012 4th International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2012 - Phuket, Thailand
Duration: 2012 Jul 242012 Jul 26

Publication series

NameProceedings - 2012 4th International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2012

Conference

Conference2012 4th International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2012
CountryThailand
CityPhuket
Period12-07-2412-07-26

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications

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    Lin, Y. C., & Chiang, P. J. (2012). Quantitative analysis of vascular structures using image processing. In Proceedings - 2012 4th International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2012 (pp. 278-283). [6274355] (Proceedings - 2012 4th International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2012). https://doi.org/10.1109/CICSyN.2012.59