Segmentation of Retinal Layers in OCT Images of the Mouse Eye Utilizing Polarization Contrast
- 1.3k Downloads
Retinal layer segmentation is crucial for the interpretation and visualization of optical coherence tomography (OCT) image data. In this work we utilized a polarization-sensitive OCT system to enhance the segmentation of the retinal pigment epithelium in the mouse retina together with the segmentation of five additional retinal surfaces. Hereby, retinal layers are segmented on a tomogram basis using a graph-based approach in the reflectivity images as well as the cross-polarization images. Thickness changes in the superoxide dismutase 1 (SOD1) knock-out mouse model were assessed and compared to a control group and revealed a thinning of the total and outer retina. Pathological drusen-like lesions were identified in the outer retina. Incorporating additional image contrast offered by the functional extensions of OCT into traditional layer segmentation approaches proved to be valuable. The proposed approach might be extended with other contrast channels such as OCT angiography.
- 12.McDonough, K., et al.: A neural network approach to retinal layer boundary identification from optical coherence tomography images. In: 2015 IEEE CIBCB, pp. 1–8 (2015)Google Scholar
- 15.Schottenhamml, J., et al.: Oct-octa segmentation: a novel framework and an application to segment bruch’s membrane in the presence of drusen. Invest. Ophthalmol. Vis. Sci. 58(8), 645 (2017)Google Scholar