3D reconstruction of carotid artery in B-mode ultrasound image using modified template matching based on ellipse feature

I. Made Gede Sunarya*, Eko Mulyanto Yuniarno, Tri Arief Sardjono, Ismoyo Sunu, P. M. A. (Peter) van Ooijen, I. Ketut Eddy Purnama

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Detection of vascular areas using B-mode ultrasound is required for automated applications such as registration and navigation in medical operations. The limitations of Ultrasound imaging are the requirement of sonographer's skills, expertise, and also knowledge when making data acquisition. It also influences the quality of the images. Carotid atherosclerosis can be treated with carotid artery stenting. The starting point of needle injection cannot be determined with certainty. The position of the arteries is in the body, therefore, determining the starting point of needle injection is done by estimation only and cannot be certainly determined. To be able to determine it, the first step needed is to determine the location of the carotid artery. We propose a 3D reconstruction of carotid artery using a modified template matching based on ellipse feature to determine it. It is processed using the procedure of data acquisition, preprocessing, segmentation, outlier selection of ellipse parameter fitting, visualisation. The proposed procedure with preprocessing produces the highest accuracy compared to the template matching method and the Hough Circle method with an accuracy value of 99.41% and has the smallest standard deviation value of 1.05. The best polynomial fitting results for all data is the polynomial equation on 22nd order with the mean error value of 0.26303.

Original languageEnglish
Number of pages12
JournalComputer methods in biomechanics and biomedical engineering-Imaging and visualization
Volume8
Issue number3
DOIs
Publication statusPublished - 23-Nov-2019

Keywords

  • Carotid artery
  • 3D reconstruction
  • ellipse feature
  • segmentation
  • 3D visualisation
  • LUMEN SEGMENTATION

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