Automated and ImageJ thresholding algorithm-based analysis of macular vessel density in diabetic patients.
Purpose: To assess the macular vessel density (VD) on optical coherence tomography angiography (OCT-A) using proprietary software (automated) and image processing software (manual) in diabetic patients.Methods: In a retrospective study, OCT-A images (Triton, TOPCON Inc.) of type 2 diabetics presenti...
| Publicado en: | Indian Journal of Ophthalmology Vol. 70; no. 6; pp. 2050 - 2057 |
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| Autores principales: | , , , , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
Wolters Kluwer India Pvt Ltd
Jun2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=157332462&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 157332462 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03014738 1BRZ jtl: Indian Journal of Ophthalmology issn: 03014738 maglogo: N pubinfo: dt: Jun2022 vid: 70 iid: 6 pid: 16919 pub: Wolters Kluwer India Pvt Ltd artinfo: ui: 157332462 157332462 NLM35647980 157332462 10.4103/ijo.IJO_74_22 NLM35647980 157332462 ppf: 2050 ppct: 7 formats: tig: atl: Automated and ImageJ thresholding algorithm-based analysis of macular vessel density in diabetic patients. aug: au: Kumawat, Devesh Chawla, Rohan Shah, Pooja Sharma, Anu Sachan, Anusha Pandey, Veena affil: Dr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi sug: subj: Diabetes Mellitus Diabetic Retinopathy Diagnosis Angiography Methods Algorithms Retina Retrospective Design Human ab: Purpose: To assess the macular vessel density (VD) on optical coherence tomography angiography (OCT-A) using proprietary software (automated) and image processing software (manual) in diabetic patients.Methods: In a retrospective study, OCT-A images (Triton, TOPCON Inc.) of type 2 diabetics presenting to a tertiary eye care center in North India between January 2018 and December 2019 with or without nonproliferative diabetic retinopathy (NPDR) and with no macular edema were analyzed. Macular images of size 3 × 3 mm were binarized with global thresholding algorithms (ImageJ software). Outcome measures were superficial capillary plexus VD (SCP-VD, automated and manual), deep capillary plexus VD (DCP-VD, manual), and correlation between automated and manual SCP-VD.Results: OCT-A images of 89 eyes (55 patients) were analyzed: no diabetic retinopathy (NoDR): 29 eyes, mild NPDR: 29 eyes, and moderate NPDR: 31 eyes. Automated SCP-VD did not differ between NoDR and mild NPDR (P = 0.69), but differed between NoDR and moderate NPDR (P = 0.014) and between mild and moderate NPDR (P = 0.033). Manual SCP-VD (Huang and Otsu methods) did not differ between the groups. Manual DCP-VD differed between NoDR and mild NPDR and between NoDR and moderate NPDR, but not between mild and moderate NPDR with both Huang (P = 0.024, 0.003, and 0.51, respectively) and Otsu (P = 0.021, 0.006, and 0.43, respectively) methods. Automated SCP-VD correlated moderately with manual SCP-VD using Huang method (r = 0.51, P < 0.001) with a mean difference of -0.01% (agreement limits from -6.60% to +6.57%).Conclusion: DCP-VD differs consistently between NoDR and NPDR with image processing, while SCP-VD shows variable results. Different thresholding algorithms provide different results, and there is a need to establish consensus on the most suited algorithm. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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