Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/14448
Title: | Retinal OCT Image Segmentation Using Fuzzy Histogram Hyperbolization and Continuous Max-Flow |
Other Titles: | IEEE International Symposium on Computer-Based Medical Systems |
Authors: | Dodo, B Li, Y Liu, X |
Keywords: | Retinal OCT;Fuzzy Histogram Hyperbolization;Speckle Noise;Graph-Cut;Continuous Max-Flow |
Issue Date: | 2017 |
Citation: | 2017 |
Abstract: | The segmentation of retinal layers is vital for tracking progress of medication and diagnosis of various eye diseases. To date many methods for the analysis exist, however the speckle noise and shadows of retinal blood vessel remains a challenge, with negative influence on the performance of segmentation algorithms. Previous attempts have been focused on image preprocessing or developing sophisticated models for segmentation to address this problem, but it still remains an area of active research. In this paper we propose a simple yet efficient and computationally inexpensive method by using fuzzy histogram hyperbolization for enhancement technique, and continuous maxflow for segmentation of four retinal layers (Inner Limiting membrane, Retinal Nerve Fibre Layer, Outer segment and the Retinal Pigment Epithelium). The results show improvement in segmentation performance. |
URI: | http://bura.brunel.ac.uk/handle/2438/14448 |
Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers |
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