Abstract
The assessment of choroidal thickness from optical coherence tomography (OCT) images of the human choroid is an important clinical and research task, since it provides valuable information regarding the eye's normal anatomy and physiology, and changes associated with various eye diseases and the development of refractive error. Due to the time consuming and subjective nature of manual image analysis, there is a need for the development of reliable objective automated methods of image segmentation to derive choroidal thickness measures. However, the detection of the two boundaries which delineate the choroid is a complicated and challenging task, in particular the detection of the outer choroidal boundary, due to a number of issues including: (i) the vascular ocular tissue is non-uniform and rich in non-homogeneous features, and (ii) the boundary can have a low contrast. In this paper, an automatic segmentation technique based on graph-search theory is presented to segment the inner choroidal boundary (ICB) and the outer choroidal boundary (OCB) to obtain the choroid thickness profile from OCT images. Before the segmentation, the B-scan is pre-processed to enhance the two boundaries of interest and to minimize the artifacts produced by surrounding features. The algorithm to detect the ICB is based on a simple edge filter and a directional weighted map penalty, while the algorithm to detect the OCB is based on OCT image enhancement and a dual brightness probability gradient. The method was tested on a large data set of images from a pediatric (1083 B-scans) and an adult (90 B-scans) population, which were previously manually segmented by an experienced observer. The results demonstrate the proposed method provides robust detection of the boundaries of interest and is a useful tool to extract clinical data.
Highlights
The choroid is the vascular tissue located at the posterior part of the eye between the retina and the sclera
The instrument utilizes a confocal scanning laser ophthalmoscope to automatically track the eye in real-time, and this function was active during the examination to achieve an average of 30 B-scans per each radial optical coherence tomography (OCT) image
#198228 - $15.00 USD Received 24 Sep 2013; revised 31 Oct 2013; accepted 4 Nov 2013; published 11 Nov 2013 features and heterogeneous in structure, which can be difficult to discriminate from the actual choroid-sclera boundary, and (iii) the shape of the choroid presents greater thickness variations and asymmetries [6] than the retinal layers [54]. We have addressed these detection problems using a graph-theory approach, similar to that proposed by Chiu et al [38] to segment the retinal layers in OCT images
Summary
The choroid is the vascular tissue located at the posterior part of the eye between the retina and the sclera. Since its first introduction in 1991, optical coherence tomography (OCT) [17] has become the standard clinical and research tool for the non-invasive cross-sectional imaging of the posterior eye [18] Studies with this technique focused on the quantification of retinal characteristics [19], recent advances in imaging techniques (i.e. real-time tracking of the eye, averaging of multiple B-scans and enhanced depth imaging (EDI) acquisition) have enabled the capture of high quality images of deeper tissues such as the choroid [7, 20]. In addition to these improvements in many of the clinical OCT instruments, a number of laboratory-based methods have been shown to further enhance the visualization of the choroid including longer wavelength light sources [21,22,23,24], the use of polarization sensitive OCT information [25, 26] and choroidal vessel angiography through a Doppler OCT system [27, 28]
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