Vascular biomarkers for diabetes and diabetic retinopathy screening
| Autor: | Huang, Fan, Abbasi-Sureshjani, Samaneh, Zhang, Jiong, Bekkers, Erik J., Dasht Bozorg, Behdad, ter Haar Romeny, Bart M., Trucco, Emanuele, MacGillivray, Tom, Xu, Yanwu |
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| Přispěvatelé: | Medical Image Analysis, Mathematical Image Analysis |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry Retinal damage Diabetic retinopathy screening Normalization (image processing) Pattern recognition SDG 3 – Goede gezondheid en welzijn medicine.disease Tortuosity SDG 3 - Good Health and Well-being Diabetes mellitus medicine cardiovascular system Artificial intelligence business |
| Zdroj: | Computational Retinal Image Analysis: Tools, Applications and Perspectives, 319-352 STARTPAGE=319;ENDPAGE=352;TITLE=Computational Retinal Image Analysis |
| DOI: | 10.1016/b978-0-08-102816-2.00017-4 |
| Popis: | The chapter describes automated quantitative vascular biomarkers in retinal fundus images for the early warning of retinal damage, as developed in the Sino-Dutch RetinaCheck project. The software implements brain-inspired algorithms, exploiting multiscale, and multiorientation geometric methods. A full pipeline is presented, including background normalization, crossing-preserving vessel enhancement, nonlinear denoising, and contextual vessel completion. The quantitative biomarkers are vessel width, vessel tortuosity, vessel bifurcation measures, and several fractal dimensions. The methods are extensively validated and show high robustness and state-of-the-art performance. |
| Databáze: | OpenAIRE |
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