Title: Semi-automated detection of aortic root in human heart MSCT images using nonlinear filtering and unsupervised clustering

Authors: Oscar Valbuena; Miguel Angel Vera; Atilio Del Mar; Felida Andreina Roa; Antonio José Bravo

Addresses: Facultad de Ciencias Básicas y Biomédicas, Universidad Simón Bolívar, Cúcuta, 540004, Colombia ' Facultad de Ciencias Básicas y Biomédicas, Universidad Simón Bolívar, Cúcuta, 540004, Colombia ' Instituto de Bioingeniería y Diagnóstico Sociedad Anónima, San Cristóbal 5001, Venezuela ' Grupo de Bioingeniería, Decanato de Investigación, Universidad Nacional Experimental del Táchira, San Cristóbal 5001, Venezuela ' Facultad de Ciencias Básicas y Biomédicas, Universidad Simón Bolívar, Cúcuta, 540004, Colombia

Abstract: A semiautomatic technique to detect the aortic root in three-dimensional multi-slice computerised tomography images is proposed. Three steps are considered: conditioning, filtering, and detection. The conditioning is based on multi-planar reconstruction and it is required for reformatting the information to orthogonal planes to the aortic root. During the filtering, three nonlinear filters based on similarity enhancement, median and weighted median are considered to reduce noise and enhance the reformatted images. In the detection, the filtered volumes are processed with a clustering technique. Dice score, the point-to-mesh and the Hausdorff distances are used to compare the obtained results with respect to ground truth traced by a cardiologist. A clinical dataset of 90 volumes from 45 patients is used to validate the technique. The maximum Dice score (0.92), the minimum average point-to-mesh distance (0.96 mm) and the minimum average Hausdorff distance (4.80 mm) are obtained during preprocessed volumes segmentation using similarity enhancement.

Keywords: human heart; aortic root; multi-slice computerised tomography; MSCT; segmentation; similarity enhancement; weighted median; unsupervised clustering.

DOI: 10.1504/IJBET.2021.10037466

International Journal of Biomedical Engineering and Technology, 2021 Vol.35 No.4, pp.295 - 317

Received: 06 Sep 2017
Accepted: 27 Feb 2018

Published online: 29 Apr 2021 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article