C. Jeyakarthikeyan ¹, C. Jayakumari ²

Affiliations
1 SSNCE, Chennai - 603110, Tamil Nadu, IN
2 Middle East College, Oman

Abstract

Objective: The authors propose to develop a new image filter technique based on bit planes of retinal fundus image to enhance the image preprocessing task. Method/Statistical Analysis: The most two significant bit planes of an image are taken and preprocessed using an image matrix filter. The image arithmetic operations are used to enhance the new filter. The sample graded portions of each of the 60 AMD images are processed to study this filter technique. The effect of the technique is studied with basic statistics tests using mean, median, standard deviation and t-test, testing on column vectors of images. Findings: The basic statistic measures such as mean, median, range and standard deviations are applied on image pixel data before and after application of filter technique. The standard deviation of post filtered graded portions of the image shows a higher value than that of the graded portions of unfiltered image, indicating that there is a positive effect of filtering. The effectiveness of the technique is also studied with a statistical paired t-test. This test is used to find the effect of processing bit planes of the respective graded pixel portions in the image samples. This statistical evidence of the result reveal that the null hypothesis is rejected to conclude that image is enhanced for further processing of drusen spots in AMD. Application/Improvements: The least bit planes of the graded portions of the image may be furthur processed to enable easier classification of different types of drusens in the image.

Keywords

Age-related Macular Degeneration, Bit Plane, Drusen, Filter, Fundus Image.

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S. Mookambigai ¹, C. Jayakumari ²

Affiliations
1 Department of Research and Development Centre, Agurchand Manmull Jain College, Meenambakkam, Chennai – 600114, Tamil Nadu, IN
2 Middle East College (MEC), Knowledge Oasis Muscat P.B. No. 79, Al Rusayl, Muscat 124, Oman, (Affiliated to Coventry University, UK)

Abstract

Objectives: The aim of the study is to review working principles of Optical Coherence Tomography (OCT), and to describe its use in the diagnosis and management of various retinal diseases in medical field. Methods/Analysis: Qualitative analysis such as Morphological alterations, Anomalous structures, 3-D & C-scan studies, increased and decreased reflectivity. Quantitative analysis includes retinal layer thickness measurement, volume and mapping. Interpretations of Spectral Domain OCT (SD-OCT), images to analyze abnormalities in retinal layers in z-depth or 3D scan or C-scan. SD-OCT visualizes ocular structures of retinal diseases in unprecedented 3-D views. It provides an accurate analytic and synthetic study of Retinal Deformations, Retinal edema, Macular Pucker, Macular hole, irregular foveal depression. Findings: In 3-D studies of macular cube, B-scan of the retinal profile gives an absolute representation of optical tissue for the study and measurement. The thickness of Fovea is about 160 - 180 microns and the resolving power measured using the A-scan study is under 4 microns. In case of ARMD-Age- related Macular degeneration (Drusen), the yellow deposits in between RPE (Retinal Pigment Epithellium) and Choroid layer is identified clearly. OCT finds that the RPE atrophy is dynamic and also the external membrane or layers of the retina. In case of Pseudo-vitelliform macular degeneration OCT shows a nontransparent yellow-orange sub-retinal deposit and a central retinal detachment. For Glaucoma disease OCT provides accurate images and this allows us to understand the physical structure (morphology) of the optical disc and the peripapillary nerve strands. In Central Serous Chorio Retinopathy (CSCR) OCT display a little gaps/discontinuity in the RPE at the dispersion location within the serous RPE separation. Various diffusion points shall be visible around the area towards Bruch’s membrane around RPE. Cystoid Macular Edema displayed by showing destruction of the Muller glia cells, leading to cystoid cavity formation inside the retina. Novelty/improvement: Future work is towards the study of determining and analyzing macular degeneration by SD-OCT tool to diagnose possible symptoms for the disease by identifying affected retinal layers through OCT images using improved mmethodologies like image pre-processing, segmentation and classification based on specific algorithm in neural networks.

Keywords

Interpretation-Retinal SD-OCT Images, OCT Generation, OCT Retinal Layers, OCT Retinal Diseases, OCT in All Fields

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