Light intensity matching between different intravascular optical coherence tomography systems

Conference Paper (2016)
Author(s)

Shengnan Liu (Leiden University Medical Center)

Jeroen Eggermont (Leiden University Medical Center)

Shimpei Nakatani (Sakurabashi Watanabe Hospital)

Boudewijn P.F. Lelieveldy (Leiden University Medical Center, TU Delft - Pattern Recognition and Bioinformatics)

Jouke Dijkstra (Leiden University Medical Center)

Research Group
Pattern Recognition and Bioinformatics
DOI related publication
https://doi.org/10.1117/12.2209311
More Info
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Publication Year
2016
Language
English
Research Group
Pattern Recognition and Bioinformatics
Pages (from-to)
96893D-1-96893D-7
ISBN (print)
9781628419245

Abstract

Currently two commercial intravascular optical coherence tomography (IVOCT) systems are available: Illumien Optis from St. Jude Medical (SJM) and Lunawave from Terumo. Both systems store the light intensity data in a raw vendor specic polar format. However, whereas SJM uses 16-bits per pixel Terumo uses 8-bits meaning the intensity values are in dierent ranges. This complicates quantitative light intensity based analysis when comparing results based on data from both systems. Therefore, this work aims to find an intensity transformation function from Terumo's 8-bit OFDI data to SJM's 16-bit range. The data consists of 8 pullbacks, 4 acquired with each system in the same arteries of 2 dierent patents pre- and post-stenting implantation. A total of 133 matching sections without stent struts from the two sets of pullbacks were identied based on landmarks such as side-branches and calcied regions. Since the main region of interest in the image is the tissue region only the pixels within 2mm behind the lumen border are used. In order to match the SJM data range, the Terumo data
was rescaled and cumulative distribution functions (CDF) were calculated based on the histogram distributions. Comparing these CDFs, the transformation function can be determined. Application of this transformation function not only improves the visual similarity of matching slices it can also be used for further quantitative analysis.

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