3 May 2012 Evaluating the effectiveness of treatment of corneal ulcers via computer-based automatic image analysis
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Corneal Ulcers are a common eye disease that requires prompt treatment. Recently a number of treatment approaches have been introduced that have been proven to be very effective. Unfortunately, the monitoring process of the treatment procedure remains manual and hence time consuming and prone to human errors. In this research we propose an automatic image analysis based approach to measure the size of an ulcer and its subsequent further investigation to determine the effectiveness of any treatment process followed. In Ophthalmology an ulcer area is detected for further inspection via luminous excitation of a dye. Usually in the imaging systems utilised for this purpose (i.e. a slit lamp with an appropriate dye) the ulcer area is excited to be luminous green in colour as compared to rest of the cornea which appears blue/brown. In the proposed approach we analyse the image in the HVS colour space. Initially a pre-processing stage that carries out a local histogram equalisation is used to bring back detail in any over or under exposed areas. Secondly we deal with the removal of potential reflections from the affected areas by making use of image registration of two candidate corneal images based on the detected corneal areas. Thirdly the exact corneal boundary is detected by initially registering an ellipse to the candidate corneal boundary detected via edge detection and subsequently allowing the user to modify the boundary to overlap with the boundary of the ulcer being observed. Although this step makes the approach semi automatic, it removes the impact of breakages of the corneal boundary due to occlusion, noise, image quality degradations. The ratio between the ulcer area confined within the corneal area to the corneal area is used as a measure of comparison. We demonstrate the use of the proposed tool in the analysis of the effectiveness of a treatment procedure adopted for corneal ulcers in patients by comparing the variation of corneal size over time.
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Nesreen A. Otoum, Nesreen A. Otoum, Eran A. Edirisinghe, Eran A. Edirisinghe, Harminder Dua, Harminder Dua, Lana Faraj, Lana Faraj, "Evaluating the effectiveness of treatment of corneal ulcers via computer-based automatic image analysis", Proc. SPIE 8436, Optics, Photonics, and Digital Technologies for Multimedia Applications II, 84360D (3 May 2012); doi: 10.1117/12.922620; https://doi.org/10.1117/12.922620


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