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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprs-archives-XLII-4-W6-85-2017</article-id>
<title-group>
<article-title>ROI DETECTION AND VESSEL SEGMENTATION IN RETINAL IMAGE</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Sabaz</surname>
<given-names>F.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Atila</surname>
<given-names>U.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Karabuk University, Dept. of Computer Engineering, 78050, Karabuk, Turkey</addr-line>
</aff>
<pub-date pub-type="epub">
<day>13</day>
<month>11</month>
<year>2017</year>
</pub-date>
<volume>XLII-4/W6</volume>
<fpage>85</fpage>
<lpage>89</lpage>
<permissions>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-4-W6-85-2017.html">This article is available from https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-4-W6-85-2017.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-4-W6-85-2017.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-4-W6-85-2017.pdf</self-uri>
<abstract>
<p>Diabetes disrupts work by affecting the structure of the eye and afterwards leads to loss of vision. Depending on the stage of disease
that called diabetic retinopathy, there are sudden loss of vision and blurred vision problems. Automated detection of vessels in retinal
images is a useful study to diagnose eye diseases, disease classification and other clinical trials. The shape and structure of the vessels
give information about the severity of the disease and the stage of the disease. Automatic and fast detection of vessels allows for a
quick diagnosis of the disease and the treatment process to start shortly. ROI detection and vessel extraction methods for retinal image
are mentioned in this study. It is shown that the Frangi filter used in image processing can be successfully used in detection and
extraction of vessels.</p>
</abstract>
<counts><page-count count="5"/></counts>
</article-meta>
</front>
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