Depths-encoded angular compounding for speckle reduction in optical coherence tomography

Zhaoyuan Cao; Jie Qian; Xinjian Chen; Jianhua Mo

doi:10.1117/12.2214620

8 March 2016 Depths-encoded angular compounding for speckle reduction in optical coherence tomography

Zhaoyuan Cao, Jie Qian, Xinjian Chen, Jianhua Mo

Author Affiliations +

Proceedings Volume 9697, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XX; 96972V (2016) https://doi.org/10.1117/12.2214620
Event: SPIE BiOS, 2016, San Francisco, California, United States

Abstract

Optical coherence tomography (OCT) is one of the successful inventions in medical imaging as a clinic routine in the past decades. This imaging technique is based on low coherence interferometer and consequently suffers from speckle noise inherently, which can degrade image quality and obscure micro-structures. Therefore, effective speckle reduction techniques have been always desired and researched since optical coherence tomography was invented. In this study, we proposed an angular compounding method to reduce speckle noise of OCT image. Two different angular light paths are created on the sample arm using two beam splitters. The epi-detection scheme creates three different combinations of the two angular light paths above, which produce three images in single B-scan. To compound these three images, these three images are separated in depth by delaying one light path relative to the other. Compared to those reported angular compounding methods, our method showed an advantage of faster imaging speed. This method was evaluated on an artificial eye model. The results demonstrated a 1.46-fold improvement in speckle contrast.

Citation Download Citation

Zhaoyuan Cao, Jie Qian, Xinjian Chen, and Jianhua Mo "Depths-encoded angular compounding for speckle reduction in optical coherence tomography", Proc. SPIE 9697, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XX, 96972V (8 March 2016); https://doi.org/10.1117/12.2214620

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