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A new combined method based on curvelet transform and morphological operators for automatic detection of foveal avascular zone

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Abstract

In order to achieve early detection of diabetic retinopathy (DR) for the sake of preventing from blindness, regular screening using retinal photography is necessary. Abnormalities of DR do not have uniform distribution over the retina. Certain types of abnormalities usually occur in specific areas on the retina. The distance between lesions, such as micro-aneurysms, and the foveal avascular zone (FAZ) is a useful feature for later analysis and grading of DR. In this paper, a new fully automatic system is presented to find the location of FAZ in fundus fluorescein angiogram photographs. The method is based on two procedures: digital curvelet transform (DCUT) and morphological operations. Firstly, end points of vessels are detected based on vessel segmentation using DCUT. By connecting these points in the selected region of interest, FAZ region is extracted. Secondly, vessels are subtracted from the retinal image, and morphological dilatation and erosion are applied on the resulted image. By choosing an appropriate threshold, FAZ region is detected. The final FAZ region is extracted by performing logical AND between two segmented FAZ. Our experiments show that the system achieves, respectively, the specificity and sensitivity of (>98 and >96 %) for normal stage, for mild/moderate non-proliferative DR (NPDR) (>98, and >95 %) and for Sever NPDR + PDR (>97 and >93 %).

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Authors and Affiliations

  1. Biomedical Engineering Department, Medical Image & Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

    Shirin Hajeb Mohammad Alipour & Hossein Rabbani

  2. Ophthalmology Department School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

    Mohammadreza Akhlaghi

Authors
  1. Shirin Hajeb Mohammad Alipour
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  2. Hossein Rabbani
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  3. Mohammadreza Akhlaghi
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Corresponding author

Correspondence to Hossein Rabbani.

Appendix

Appendix

In order to show an estimation of the interobserver variability of proposed procedure in this paper for FAZ detection and intra-observer too, the overlap between segmentations for all ground truth images in this study is showed in Table 4 that could be compared directly to the quantitative overlap index reported in Table 1 for checking the lack of outlier cases.

Table 4 Overlapping ratio between results of morphological-based and curvelet-based methods, and inter- and intra-observer overlapping ratio for FFA images in this study
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In order to group the results for each subpopulation of DR (normal, Mild/Moderate NPDR and Severe NPDR + PDR), the overlapping ratio, specificity and sensitivity of all data in each group can be seen in Fig. 16.

Fig. 16
figure 16

The plot of overlapping ratio, specificity and sensitivity of our FAZ detection method for each patient in each group (normal, mild/moderate NPDR and Sever NPDR + PDR)

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Hajeb Mohammad Alipour, S., Rabbani, H. & Akhlaghi, M. A new combined method based on curvelet transform and morphological operators for automatic detection of foveal avascular zone. SIViP 8, 205–222 (2014). https://doi.org/10.1007/s11760-013-0530-6

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