Leak detection optimisation on retina fluorescein angiography images using phase stretch transform for malaria retinopathy
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Abstract
Malarial Retinopathy (MR) is indicated by retina alteration such as white dots occurrence which is caused by malaria. Leak detection is a key factor of MR’s early diagnosis. Inconsistent size and shape of the leakages with the colour contrast that relatively similar with the background. Leak detection’s algorithm is one of the most complex algorithms on the fundus image analysis field. Therefore, improving performance in the leakage detection is essential. This study focuses on automated leakage detection on fluorescein angiography (FA) images. The methods used in this study are vessel segmentation, saliency detection, phase stretch transform (PST), optic disk removal and leak detection to extract some features which then classified to correctly validate the leak. From 20 patient data large focal leak images with 31 leak points, 28 of them have been correctly detected. So, the experiment produced the accuracy and specificity of 0.98 and 0.9, respectively. With the proposed method of this study, there is a potential to enhance the knowledge on MR field in the future.
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References
H. Reyburn, R. Mbatia, C. Drakeley, I. Carneiro, E. Mwakasungula, Mw erinde, K. Saganda, J. Shao, A. Kitua, R. Olomi, B. M. Green-wood, C. J. Whitt, Overdiagnosis of malaria in patients with severe febrile illness in Tanzania: a prospective study, BMJ 329 (2004) 1212-1217.
I. F. Schemann, Doumbo, D. Malvy, L. Traore, A. Kone, T. Sidibe, M. Keita, Ocular lesions associated with malaria in children in Mali, Am. J. Trop. Med. Hyg. 67 (2002) 61-63.
F. Poncet, De la retino-choroidite palustre, Ann. Ocul. 79 (1878) 201-218.
S. Lewallen, T. E. Taylor, M. E. Molyneux, B. A. Wills, Courtright Ocular fundus ndings in Malawian children with cerebral malaria, Ophthalmol. 100 (1993) 857-861.
T. Hnscheid, Diagnosis of malaria: a review of alternatives to conventional microscopy, Clin. Lab. Haematol. 21 (1999) 235-245.
V. A. White, S. Lewallen, N. A. V. Beare, M. E. Molyneux, T. E. Taylor, Retinal pathology of pediatric cerebral malaria in Malawi, PloS One 4 (2009) e4317.
K. Khurshid et al., Comparison of Niblack inspired Binarization methods for ancient documents, SPIE Conference, vol. 7247, 2009.
S. Dithmar and F. Holz. Fluorescence angiography in ophthalmology: Fluorescein angiography, indocyanine green angiography, fundus autofluorescence. Springer-Verlag Berlin Heidelberg, 2008.
N. Beare, S. Glover and M. Molyneux, Malarial retinopathy in cerebral malaria, Am. J. Trop. Med. Hyg. 80 (2009) 171.
Y. Zhao, I. J. C. MacCormick, D. G. Parry, S. Leach, N. A. V. Beare, S. P. Harding and Y. Zheng, Automated detection of leakage in fluorescein angiography images with application to malarial retinopathy, Sci. Rep. 5 (2015) 1–12.
Y. Zhao, Y. Zheng, Y. Liu, J. Yang, Y. Zhao, D. Chen and Y. Wang, Intensity and Compactness Enabled Saliency Estimation for Leakage Detection in Diabetic and Malarial Retinopathy, IEEE Trans. Med. Imaging 36 (2017) 51–63.
K. Firdausy and K. Z. Widhia Oktoeberza, Segmentation of optic disc using dispersive phase stretch transform, 6th Int. Annu. Eng. Semin. Ina., 154–158, 2017.
M. H. Asghari and B. Jalali, Physics-inspired image edge detection, in Signal and Information Processing (GlobalSIP), 2014 IEEE Global Conference, 293-296, 2014.