Development of an innovative technology to segment luminal borders of intravascular ultrasound image sequences in a fully automated manner.

Authors:
Abouzar Moshfegh
Abouzar Moshfegh
Macquarie University
Ashkan Javadzadegan
Ashkan Javadzadegan
University of Sydney
Australia
Maryam Mohammadi
Maryam Mohammadi
University of Tabriz
Iran
Shaokoon Cheng
Shaokoon Cheng
Prince of Wales Medical Research Institute
Ralph Martins
Ralph Martins
School of Medical Sciences

Comput Biol Med 2019 May 14;108:111-121. Epub 2019 Mar 14.

Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, 2109, Australia; School of Exercise, Biomedical and Health Sciences, Edith Cowan University, Perth, Australia.

Although intravascular ultrasound (IVUS) is the commonest intravascular imaging modality, it still is inefficient for clinical use as it requires laborious manual analysis. This study demonstrates the feasibility of a near real-time fully automated technology for accurate identification, detection, and quantification of luminal borders in intravascular images. This technology uses a combination of the novel approaches of a self-tuning engine, dynamic and static masking systems, radar-wise scan, and contour correction cycle method. The performance of the computer algorithm developed based on this technology was tested on a sequence of IVUS and True Vessel Characterization (TVC) images obtained from the left anterior descending (LAD) artery of 6 patients with coronary artery disease. The accuracy of the algorithm was evaluated by comparing luminal borders traced manually with those detected automatically. The processing time of the developed algorithm was also tested on a Dell laptop with an Intel Core i7-8750H Processor (4.1 GHz with 6 cores, 9 MB Cache). Linear regression and Bland-Altman analyses indicated high correlation between manual and automatic tracings (Y = 0.80 × X+1.70, R = 0.88 & 0.67 ± 1.31 (bias±SD)). Whereas analysis of 2000 IVUS images using one CPU core with a 30% load took 23.12 min, the same analysis using six CPU cores with 90% load took 1.0 min. The performance, accuracy, and speed of the presented state-of-the-art technology demonstrates its capacity for use in clinical settings.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.compbiomed.2019.03.008DOI Listing
May 2019
3 Reads

Publication Analysis

Top Keywords

luminal borders
12
borders intravascular
8
intravascular ultrasound
8
fully automated
8
technology
5
bias±sd analysis
4
true vessel
4
067 ± 131 bias±sd
4
ivus true
4
sequence ivus
4
technology tested
4
analysis 2000
4
tested sequence
4
vessel characterization
4
tvc images
4
anterior descending
4
descending lad
4
lad artery
4
y = 080 × x+170 r = 088
4
left anterior
4

Similar Publications