Enhanced optical coherence tomography imaging using a histogram-based denoising algorithm

Keo-Sik Kim; Hyoung-Jun Park; Hyun Seo Kang

doi:10.1117/1.OE.54.11.113110

25 November 2015 Enhanced optical coherence tomography imaging using a histogram-based denoising algorithm

Keo-Sik Kim, Hyoung-Jun Park, Hyun Seo Kang

Author Affiliations +

Optical Engineering, Vol. 54, Issue 11, 113110 (November 2015). https://doi.org/10.1117/1.OE.54.11.113110

Abstract

A histogram-based denoising algorithm was developed to effectively reduce ghost artifact noise and enhance the quality of an optical coherence tomography (OCT) imaging system used to guide surgical instruments. The noise signal is iteratively detected by comparing the histogram of the ensemble average of all A-scans, and the ghost artifacts included in the noisy signal are removed separately from the raw signals using the polynomial curve fitting method. The devised algorithm was simulated with various noisy OCT images, and <87% of the ghost artifact noise was removed despite different locations. Our results show the feasibility of selectively and effectively removing ghost artifact noise.

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Keo-Sik Kim, Hyoung-Jun Park, and Hyun Seo Kang "Enhanced optical coherence tomography imaging using a histogram-based denoising algorithm," Optical Engineering 54(11), 113110 (25 November 2015). https://doi.org/10.1117/1.OE.54.11.113110

Published: 25 November 2015

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