۳D intra-retinal layer segmentation of OCT data using modified live wire algorithm

Image segmentation is the process of dividing a digital image into sets of pixels. Its approaches are two types: automated and interactive. In contrast to automated methods, interactive algorithms, such as live wire with a core in graph theory, do not need user assistance and provide completecontrol to the user, hence they are a desirable approach in many medical applications. Particularly, optical coherence tomography (OCT) is a powerful method for imaging the retinal layers. Towards attaining a ۳D version of live wire algorithm, which is not as simple as the ۲D case, this paper makes a step forward. We develop existing versions of this algorithms. We experiment over OCT data of ۱۳ eye patients and demonstrate how they improve image segmentation of different retinal layers. Moreover, we show the good effect of two different algorithms of noise reduction on OCTimages on the performance of modified live wire algorithm

Keywords:

Optical Coherence Tomography , Image segmentation , automatic method , interactive method , ۲D boundary , active learning.