Publication Type : Conference Proceedings
Publisher : Proceedings of the International Conference on Soft Computing Systems
Source : Proceedings of the International Conference on Soft Computing Systems, Springer (2016)
Url : http://link.springer.com/chapter/10.1007/978-81-322-2674-1_20
ISBN : 9788132226741
Campus : Coimbatore
School : School of Engineering
Center : CIR
Department : Computer Science
Year : 2016
Abstract : The aim of this work is to identify the morphological patterns associated with macular leaks for diabetic maculopathy from spectral-domain optical coherence tomography (SD-OCT) a noninvasive technique and fundus fluorescein angiogram (FFA) an invasive technique. Here, an attempt has been made to identify the morphological pattern of SD-OCT images, which has association with FFA images affected by diabetic maculopathy based on conformal mapping. The preprocessing step consists of removing the speckle noise using different low-pass filters; we found that wavelet filters are efficient. Out of the 60 eyes, we were able to detect pathologies like micro-cysts in around 52 eyes which resulted in an accuracy of ~87 %. The results also showed that when SD-OCT image look normal, the conformal mapping showed angiogram leakages as micro-cysts. This is the first attempt toward correlating the features of two different modalities in retinal imaging from an image processing perspective.
Cite this Research Publication : T. R. Swapna, Chakraborty, C., and Narayanankutty, K. A., “Correlated Analysis of Morphological Patterns Between SD-OCT and FFA Imaging for Diabetic Maculopathy Detection: Conformal Mapping-Based Approach”, in Proceedings of the International Conference on Soft Computing Systems, 2016.