|International Journal of Computer Applications
|Foundation of Computer Science (FCS), NY, USA
|Volume 128 - Number 10
|Year of Publication: 2015
|Authors: Chandrappa S., Dharmanna Lamani, S. Jagadeesha, Ranjan Kumar H.S.
Chandrappa S., Dharmanna Lamani, S. Jagadeesha, Ranjan Kumar H.S. . Segmentation of Retinal Nerve Fiber Layer in Optical Coherence Tomography (OCT) Images using Statistical Region Merging Technique for Glaucoma Screening. International Journal of Computer Applications. 128, 10 ( October 2015), 32-35. DOI=10.5120/ijca2015906658
The Retinal Nerve Fiber Layer thickness is one of the main clinical parameter used to diagnose glaucoma eye disease. The thickness of the RNFL decreases as the intraocular pressure inside the eye increases. Decrease in RNFL thickness or damages to RNFL due to high intraocular pressure leads to Glaucoma. The present work provides a technique for the segmentation of Retinal Nerve Fiber Layer (RNFL) from the Optical Coherence Tomography (OCT) images. First, OCT image is pre-processed then RNFL in OCT is segmented by statistical region merging algorithm. The segmented RNFL is refined using morphological operations such as dilation and erosion. At the end, segmented RNFL is extracted by developed algorithm. The developed technique is tested with 50 RNFL images. The result shows the exact boundaries of RNFL and segmented portion of the RNFL. Segmented RNFL can be used to find the thickness of RNFL for detection of glaucoma.