Classification of white and gray matter using two-parameter model based on polarization-sensitive optical coherence tomography

Danting Meng; Yong Huang; Qun Hao

doi:10.1117/12.2645157

19 December 2022 Classification of white and gray matter using two-parameter model based on polarization-sensitive optical coherence tomography

Danting Meng, Yong Huang, Qun Hao

Author Affiliations +

Proceedings Volume 12320, Optics in Health Care and Biomedical Optics XII; 123200T (2022) https://doi.org/10.1117/12.2645157
Event: SPIE/COS Photonics Asia, 2022, Online Only

Abstract

In brain imaging, it is necessary to accurately distinguish between white matter, made up of axons and their myelin sheaths, and gray matter, made up of neurons and dendrites. Traditional optical coherence tomography (OCT) utilizes the scattering properties of light from the white and gray matter, however, the accuracy is restricted by the angle between the nerve fibers and the observation plane. In this work, we used polarization-sensitive optical coherence tomography (PSOCT) system to obtain the sample's birefringence information according to phase retardation image and proposed a two-parameter classification model containing reflectivity and birefringence, test the probability of white matter and gray matter using Bayesian detection methods, and adjust the threshold to obtain the best performance. The three-dimensional (3D) volume data were divided into 16 groups on average along the A-line direction. In each group, the white matter was set as 1 and the gray matter was set as 0, thus serving as the mask of the group. By applying multi-masks to 3D data, the position of white matter can be seen accurately. As a result, twice as much white matter was determined by proposed method than conventional method. The scattering and polarization information can be displayed simultaneously by encoding the HSV(Hue, Saturation, Value) model with reflectivity, phase retardation and optical axis orientation respectively. Our proposed two-parameter classification model can be used to distinguish white and gray matter in brain and spinal cord.

Conference Presentation

Citation Download Citation

Danting Meng, Yong Huang, and Qun Hao "Classification of white and gray matter using two-parameter model based on polarization-sensitive optical coherence tomography", Proc. SPIE 12320, Optics in Health Care and Biomedical Optics XII, 123200T (19 December 2022); https://doi.org/10.1117/12.2645157

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