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Integration of spatial fuzzy clustering with level set for segmentation of 2-D angiogram

Ghalehnovi, M ; Sharif University of Technology | 2015

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  1. Type of Document: Article
  2. DOI: 10.1109/IECBES.2014.7047509
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2015
  4. Abstract:
  5. Coronary angiography is a vital instrument to detect the prevailing of vascular diseases, and accurate vascular segmentation acts a crucial role for proper quantitative analysis of the vascular tree morphological features. Level set methods are popular for segmenting the coronary arteries, but their performance is related to suitable start-up and optimum setting of regulating parameters, essentially done manually. This research presents a novel fuzzy level set procedure with the objective of segmentation of the coronary artery tree in 2-D X-ray angiography as automatically. It is clever to clearly develop from the early segmentation with spatial fuzzy grouping. The adjusting parameters of the level set evolution are projected from the upshots of fuzzy grouping. The adjusting factors of the level set are updated after a number of curve progress. These enhancements ease level set handling and clue to extra strong, exact, automatic and fast segmentation. It is revealed that the offered method can attain automatic and accurate segmentation of vascular angiograms
  6. Keywords:
  7. Extraction of the vascular tree ; Segmentation of 2-D angiography images ; Angiography ; Biomedical engineering ; Blood vessels ; Drop breakup ; Image segmentation ; Level measurement ; Active contour model ; Angiography images ; Fuzzy grouping ; Level Set method ; Vascular trees ; Numerical methods
  8. Source: IECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: "Miri, Where Engineering in Medicine and Biology and Humanity Meet", 8 December 2014 through 10 December 2014 ; December , 2015 , Pages 309-314 ; 9781479940844 (ISBN)
  9. URL: http://ieeexplore.ieee.org/document/7047509