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| dc.contributor.author | Cervantes, Jair
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| dc.contributor.author | Cervantes, Jared
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| dc.contributor.author | Garcia Lamont, Farid
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| dc.contributor.author | Yee Rendon, Arturo
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| dc.contributor.author | Espejel Cabrera, Josue
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| dc.contributor.author | Dominguez Jalili, Laura
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| dc.date.accessioned | 2023-09-20T01:01:55Z | |
| dc.date.available | 2023-09-20T01:01:55Z | |
| dc.date.issued | 2023-08-04 | |
| dc.identifier.issn | 0925-2312 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.11799/138821 | |
| dc.description.abstract | In recent years, enormous research has been carried out on the segmentation of blood vessels. Segmentation of blood vessels in retinal images is crucial for diagnosing, treating, evaluating clinical results, and early detection of eye disorders. A successful segmentation accurately reflects the blood vessels’ structure and helps obtain patterns that can be used to identify retinal disorders and diseases. Most recent research on vessel segmentation employs multiple processes to determine the appropriate segmentation. Finding the best techniques for segmentation is a complex process. In certain circumstances, it requires a thorough understanding of every step that can only be acquired through years of training. Comprehension and expertise in segmentation procedures are essential for accurate segmentation. This paper briefly introduces the segmentation of blood vessels in retinal images, describes many preprocessing and segmentation techniques, and summarizes challenges and trends. Furthermore, the limitations of the current systems will be identified. | es |
| dc.description.sponsorship | Proyecto de investigación número 6525/2022CIB, Universidad Autónoma del Estado de México | es |
| dc.language.iso | eng | es |
| dc.publisher | Neurocomputing | es |
| dc.rights | embargoedAccess | es |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0 | es |
| dc.subject | Vessel segmentation | es |
| dc.subject | Preprocessing techniques | es |
| dc.subject | Segmentation techniques | es |
| dc.subject.classification | INGENIERÍA Y TECNOLOGÍA | es |
| dc.title | A comprehensive survey on segmentation techniques for retinal vessel segmentation | es |
| dc.type | Artículo | es |
| dc.provenance | Científica | es |
| dc.road | Dorada | es |
| dc.organismo | Centro Universitario UAEM Texcoco | es |
| dc.ambito | Internacional | es |
| dc.cve.CenCos | 30401 | es |
| dc.relation.vol | 556 | |
| dc.relation.doi | https://doi.org/10.1016/j.neucom.2023.126626 |