期刊
BIOMEDICAL OPTICS EXPRESS
卷 14, 期 4, 页码 1522-1543出版社
Optica Publishing Group
DOI: 10.1364/BOE.482199Journal
关键词
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Degree of polarization uniformity (DOPU) imaging obtained by polarization-sensitive optical coherence tomography (PS-OCT) has the potential to provide biomarkers for retinal diseases. A neural network-based approach is presented to estimate the DOPU from standard OCT images. DOPU images are synthesized by the neural network and compared with ground truth DOPU images to evaluate the clinical findings. The proposed method demonstrates the potential of extending the features of retinal non-PS OCT.
Degree of polarization uniformity (DOPU) imaging obtained by polarization-sensitive optical coherence tomography (PS-OCT) has the potential to provide biomarkers for retinal diseases. It highlights abnormalities in the retinal pigment epithelium that are not always clear in the OCT intensity images. However, a PS-OCT system is more complicated than conventional OCT. We present a neural-network-based approach to estimate the DOPU from standard OCT images. DOPU images were used to train a neural network to synthesize the DOPU from single-polarization-component OCT intensity images. DOPU images were then synthesized by the neural network, and the clinical findings from ground truth DOPU and synthesized DOPU were compared. There is a good agreement in the findings for RPE abnormalities: recall was 0.869 and precision was 0.920 for 20 cases with retinal diseases. In five cases of healthy volunteers, no abnormalities were found in either the synthesized or ground truth DOPU images. The proposed neural-network-based DOPU synthesis method demonstrates the potential of extending the features of retinal non-PS OCT. (c) 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
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