Detection of retinal capillary nonperfusion in fundus fluorescein angiogram of diabetic retinopathy
| العنوان: | Detection of retinal capillary nonperfusion in fundus fluorescein angiogram of diabetic retinopathy |
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| المؤلفون: | Seyed Hossein Rasta, Shima Nikfarjam, Alireza Javadzadeh |
| المصدر: | BioImpacts, Vol 5, Iss 4, Pp 183-190 (2015) BioImpacts : BI |
| بيانات النشر: | Tabriz University of Medical Sciences, 2015. |
| سنة النشر: | 2015 |
| مصطلحات موضوعية: | medicine.medical_specialty, Fluorescein angiography, Capillary nonperfusion, Pharmaceutical Science, 02 engineering and technology, 01 natural sciences, General Biochemistry, Genetics and Molecular Biology, 010309 optics, chemistry.chemical_compound, Homomorphic filtering, Diabetic retinopathy, Ophthalmology, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, Medical imaging, Medicine, Computer vision, lcsh:QH301-705.5, Retina, lcsh:R5-920, medicine.diagnostic_test, business.industry, Image processing/analysis, Retinal, General Medicine, medicine.disease, Thresholding, medicine.anatomical_structure, chemistry, lcsh:Biology (General), Ischemic retina, Fluorescein angiogram, Diagnostic imaging, 020201 artificial intelligence & image processing, Original Article, Artificial intelligence, business, lcsh:Medicine (General) |
| الوصف: | Introduction: Retinal capillary nonperfusion (CNP) is one of the retinal vascular diseases in diabetic retinopathy (DR) patients. As there is no comprehensive detection technique to recognize CNP areas, we proposed a different method for computing detection of ischemic retina, non-perfused (NP) regions, in fundus fluorescein angiogram (FFA) images. Methods: Whilst major vessels appear as ridges, non-perfused areas are usually observed as ponds that are surrounded by healthy capillaries in FFA images. A new technique using homomorphic filtering to correct light illumination and detect the ponds surrounded in healthy capillaries on FFA images was designed and applied on DR fundus images. These images were acquired from the diabetic patients who had referred to the Nikookari hospital and were diagnosed for diabetic retinopathy during one year. Our strategy was screening the whole image with a fixed window size, which is small enough to enclose areas with identified topographic characteristics. To discard false nominees, we also performed a thresholding operation on the screen and marked images. To validate its performance we applied our detection algorithm on 41 FFA diabetic retinopathy fundus images in which the CNP areas were manually delineated by three clinical experts. Results: Lesions were found as smooth regions with very high uniformity, low entropy, and small intensity variations in FFA images. The results of automated detection method were compared with manually marked CNP areas so achieved sensitivity of 81%, specificity of 78%, and accuracy of 91%.The result was present as a Receiver operating character (ROC) curve, which has an area under the curve (AUC) of 0.796 with 95% confidence intervals. Conclusion: This technique introduced a new automated detection algorithm to recognize non-perfusion lesions on FFA. This has potential to assist detecting and managing of ischemic retina and may be incorporated into automated grading diabetic retinopathy structures. |
| اللغة: | English |
| تدمد: | 2228-5660 2228-5652 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb0205449471d2540a26196d90625357Test http://journals.tbzmed.ac.ir/BI/Manuscript/BI-5-183.pdfTest |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....fb0205449471d2540a26196d90625357 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 22285660 22285652 |
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