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Retinal vasculature extraction algorithm based on an improved and lightweight U-Net deep learning model using the dense block.

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Title: Retinal vasculature extraction algorithm based on an improved and lightweight U-Net deep learning model using the dense block.
Authors: Saha Tchinda, Beaudelaire1, beaudelairesaha@gmail.com, Tchoupou Segning, Zidane Rigasse1, tchoupouzidane14@gmail.com, Tchiotsop, Daniel1, daniel.tchiotsop@gmail.com, Tchinda, René2, ttchinda@yahoo.fr
Source: Multimedia Tools & Applications; Aug2025, Vol. 84 Issue 28, p33567-33590, 24p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 187121507
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PubType: Academic Journal
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  Data: <searchLink fieldCode="JN" term="%22Multimedia+Tools+%26+Applications%22">Multimedia Tools & Applications</searchLink>; Aug2025, Vol. 84 Issue 28, p33567-33590, 24p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=187121507
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      – Type: doi
        Value: 10.1007/s11042-024-20582-4
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      – Code: eng
        Text: English
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      – TitleFull: Retinal vasculature extraction algorithm based on an improved and lightweight U-Net deep learning model using the dense block.
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            NameFull: Saha Tchinda, Beaudelaire
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            NameFull: Tchoupou Segning, Zidane Rigasse
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              Text: Aug2025
              Type: published
              Y: 2025
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              Value: 84
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              Value: 28
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