In this paper methods and their examination results for automatic segmentation and parameterization of vessels based on spectral domain optical coherence tomography (SD-OCT) of the retina are presented. We present three strategies for morphologic image processing of a fundus image reconstructed from OCT scans. A specificity of initial image processing for fundus reconstruction is analysed. Then, the parameterization step is performed based on the vessels segmented with the proposed algorithm. The influence of various methods on the vessel segmentation and fully automatic vessel measurement is analysed. Experiments were carried out with a set of 3D OCT scans obtained from 24 eyes (12 healthy volunteers) with the use of an Avanti RTvue OCT device. The results of automatic vessel segmentation were numerically compared with those prepared manually by the medical doctor experts.
This paper presents signal processing aspects for automatic segmentation of retinal layers of the human eye. The paper draws attention to the problems that occur during the computer image processing of images obtained with the use of the Spectral Domain Optical Coherence Tomography (SD OCT). Accuracy of the retinal layer segmentation for a set of typical 3D scans with a rather low quality was shown. Some possible ways to improve quality of the final results are pointed out. The experimental studies were performed using the so-called B-scans obtained with the OCT Copernicus HR device.