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              <text>A Fusion Based Approach for Blood Vessel Segmentation from Fundus Images by Separating Brighter Optic Disc</text>
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              <text>blood vessel segmentation; fundus images; image fusion; optic disc</text>
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              <text>Abstract: In ophthalmology, blood vessel segmentation from fundus images plays a significant role in automated retinal disease screening systems. Several research papers on blood vessel segmentation suggest enhancing fundus images before segmentation significantly to improve performance. The brightness of the optic disc region in a fundus image negatively influences the enhancement of relatively darker vessel pixels. Segregation of brighter optic disc from fundus images before its enhancement is the fundamental idea behind developing the proposed framework. Initially, the optic disc is extracted from the input fundus image to form two images, one containing optical disc and the other, fundus image without optical disk. In the second stage, both the images are enhanced independently, followed by blood vessel segmentation. Finally, the segmented blood vessels from the images are fused to obtain a single image. Experiments conducted with fundus images from DRIVE, STARE, and CHASE_DB1 databases show improvement in the identification of blood vessel pixels.  2021, Pleiades Publishing, Ltd.</text>
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              <text>Wahid F.F.; Sugandhi K.; Raju G.</text>
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              <text>Pattern Recognition and Image Analysis, Vol-31, No. 4, pp. 811-820.</text>
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              <text>Pleiades journals</text>
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              <text>2021-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1134/S105466182104026X" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1134/S105466182104026X&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121700331&amp;amp;doi=10.1134%2FS105466182104026X&amp;amp;partnerID=40&amp;amp;md5=8cc07e72d2f113e780152c73e0828657" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121700331&amp;amp;doi=10.1134%2fS105466182104026X&amp;amp;partnerID=40&amp;amp;md5=8cc07e72d2f113e780152c73e0828657&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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              <text>ISSN: 10546618</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>Wahid F.F., Department of Information Technology, Kannur University, Kannur, 670567, Kerala, India; Sugandhi K., Department of Information Technology, Kannur University, Kannur, 670567, Kerala, India; Raju G., Department of Computer Science and Engineering, Christ (Deemed to Be University), Kengeri Campus, Bengaluru, 560074, India</text>
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