Detection of the Optic Nerve Head in Fundus Images of the Retina with Gabor Filters and Phase Portrait Analysis
We propose a method using Gabor filters and phase portraits to automatically locate the optic nerve head (ONH) in fundus images of the retina. Because the center of the ONH is at or near the focal point of convergence of the retinal vessels, the method includes detection of the vessels using Gabor f...
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| Veröffentlicht in: | Journal of digital imaging 2010-08, Vol.23 (4), p.438-453 |
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| creator | Rangayyan, Rangaraj M. Zhu, Xiaolu Ayres, Fábio J. Ells, Anna L. |
| description | We propose a method using Gabor filters and phase portraits to automatically locate the optic nerve head (ONH) in fundus images of the retina. Because the center of the ONH is at or near the focal point of convergence of the retinal vessels, the method includes detection of the vessels using Gabor filters, detection of peaks in the node map obtained via phase portrait analysis, and an intensity-based condition. The method was tested on 40 images from the Digital Retinal Images for Vessel Extraction (DRIVE) database and 81 images from the Structured Analysis of the Retina (STARE) database. An ophthalmologist independently marked the center of the ONH for evaluation of the results. The evaluation of the results includes free-response receiver operating characteristics (FROC) and a measure of distance between the manually marked and detected centers. With the DRIVE database, the centers of the ONH were detected with an average distance of 0.36 mm (18 pixels) to the corresponding centers marked by the ophthalmologist. FROC analysis indicated a sensitivity of 100% at 2.7 false positives per image. With the STARE database, FROC analysis indicated a sensitivity of 88.9% at 4.6 false positives per image. |
| doi_str_mv | 10.1007/s10278-009-9261-1 |
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Because the center of the ONH is at or near the focal point of convergence of the retinal vessels, the method includes detection of the vessels using Gabor filters, detection of peaks in the node map obtained via phase portrait analysis, and an intensity-based condition. The method was tested on 40 images from the Digital Retinal Images for Vessel Extraction (DRIVE) database and 81 images from the Structured Analysis of the Retina (STARE) database. An ophthalmologist independently marked the center of the ONH for evaluation of the results. The evaluation of the results includes free-response receiver operating characteristics (FROC) and a measure of distance between the manually marked and detected centers. With the DRIVE database, the centers of the ONH were detected with an average distance of 0.36 mm (18 pixels) to the corresponding centers marked by the ophthalmologist. FROC analysis indicated a sensitivity of 100% at 2.7 false positives per image. With the STARE database, FROC analysis indicated a sensitivity of 88.9% at 4.6 false positives per image.</description><identifier>ISSN: 0897-1889</identifier><identifier>EISSN: 1618-727X</identifier><identifier>DOI: 10.1007/s10278-009-9261-1</identifier><identifier>PMID: 20066466</identifier><language>eng</language><publisher>New York: Springer-Verlag</publisher><subject>Algorithms ; Diagnostic Imaging - methods ; Fundus Oculi ; Humans ; Image Interpretation, Computer-Assisted ; Imaging ; Magnetic Resonance Angiography - methods ; Medicine ; Medicine & Public Health ; Micropore Filters ; Optic Disk - diagnostic imaging ; Radiography ; Radiology ; Retina - diagnostic imaging ; Retinal Vessels - diagnostic imaging ; Retinoscopy - methods ; ROC Curve</subject><ispartof>Journal of digital imaging, 2010-08, Vol.23 (4), p.438-453</ispartof><rights>Society for Imaging Informatics in Medicine 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c500t-d8bf5417c37a51b795f37333e2f26525689d6621365d871cfefbd383a2386f3c3</citedby><cites>FETCH-LOGICAL-c500t-d8bf5417c37a51b795f37333e2f26525689d6621365d871cfefbd383a2386f3c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3046656/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3046656/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20066466$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Rangayyan, Rangaraj M.</creatorcontrib><creatorcontrib>Zhu, Xiaolu</creatorcontrib><creatorcontrib>Ayres, Fábio J.</creatorcontrib><creatorcontrib>Ells, Anna L.</creatorcontrib><title>Detection of the Optic Nerve Head in Fundus Images of the Retina with Gabor Filters and Phase Portrait Analysis</title><title>Journal of digital imaging</title><addtitle>J Digit Imaging</addtitle><addtitle>J Digit Imaging</addtitle><description>We propose a method using Gabor filters and phase portraits to automatically locate the optic nerve head (ONH) in fundus images of the retina. Because the center of the ONH is at or near the focal point of convergence of the retinal vessels, the method includes detection of the vessels using Gabor filters, detection of peaks in the node map obtained via phase portrait analysis, and an intensity-based condition. The method was tested on 40 images from the Digital Retinal Images for Vessel Extraction (DRIVE) database and 81 images from the Structured Analysis of the Retina (STARE) database. An ophthalmologist independently marked the center of the ONH for evaluation of the results. The evaluation of the results includes free-response receiver operating characteristics (FROC) and a measure of distance between the manually marked and detected centers. With the DRIVE database, the centers of the ONH were detected with an average distance of 0.36 mm (18 pixels) to the corresponding centers marked by the ophthalmologist. FROC analysis indicated a sensitivity of 100% at 2.7 false positives per image. With the STARE database, FROC analysis indicated a sensitivity of 88.9% at 4.6 false positives per image.</description><subject>Algorithms</subject><subject>Diagnostic Imaging - methods</subject><subject>Fundus Oculi</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted</subject><subject>Imaging</subject><subject>Magnetic Resonance Angiography - methods</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Micropore Filters</subject><subject>Optic Disk - diagnostic imaging</subject><subject>Radiography</subject><subject>Radiology</subject><subject>Retina - diagnostic imaging</subject><subject>Retinal Vessels - diagnostic imaging</subject><subject>Retinoscopy - methods</subject><subject>ROC Curve</subject><issn>0897-1889</issn><issn>1618-727X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqFkV1rFDEUhoModlv9Ad5I8Mar0XxMPuZGKNVtC8UWUfAuZDInuymzyZpkKv33nWXb-gHiVS7Oc56cc16EXlHyjhKi3hdKmNINIV3TMUkb-gQtqKS6UUx9f4oWRHeqoVp3B-iwlGtCqBKqfY4OGCFStlIuUPoIFVwNKeLkcV0DvtzW4PBnyDeAz8AOOES8nOIwFXy-sSsoD-AXqCFa_DPUNT61fcp4GcYKuWAbB3y1tgXwVco121DxcbTjbQnlBXrm7Vjg5f17hL4tP309OWsuLk_PT44vGicIqc2gey9aqhxXVtBedcJzxTkH5pkUTEjdDVIyyqUYtKLOg-8HrrllXEvPHT9CH_be7dRvYHAQ5zlGs81hY_OtSTaYPysxrM0q3RhO5rsIOQve3gty-jFBqWYTioNxtBHSVIwSXKq2I-r_JOeSt127c775i7xOU54vU4wksmtbzekM0T3kciolg38cmhKzi93sYzdz7GYXu9n1vP5928eOh5xngO2BMpfiCvKvn_9tvQNh37eG</recordid><startdate>20100801</startdate><enddate>20100801</enddate><creator>Rangayyan, Rangaraj M.</creator><creator>Zhu, Xiaolu</creator><creator>Ayres, Fábio J.</creator><creator>Ells, Anna L.</creator><general>Springer-Verlag</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QO</scope><scope>7RV</scope><scope>7SC</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K9.</scope><scope>KB0</scope><scope>L7M</scope><scope>LK8</scope><scope>L~C</scope><scope>L~D</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20100801</creationdate><title>Detection of the Optic Nerve Head in Fundus Images of the Retina with Gabor Filters and Phase Portrait Analysis</title><author>Rangayyan, Rangaraj M. ; Zhu, Xiaolu ; Ayres, Fábio J. ; Ells, Anna L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c500t-d8bf5417c37a51b795f37333e2f26525689d6621365d871cfefbd383a2386f3c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Algorithms</topic><topic>Diagnostic Imaging - methods</topic><topic>Fundus Oculi</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted</topic><topic>Imaging</topic><topic>Magnetic Resonance Angiography - methods</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Micropore Filters</topic><topic>Optic Disk - diagnostic imaging</topic><topic>Radiography</topic><topic>Radiology</topic><topic>Retina - diagnostic imaging</topic><topic>Retinal Vessels - diagnostic imaging</topic><topic>Retinoscopy - methods</topic><topic>ROC Curve</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rangayyan, Rangaraj M.</creatorcontrib><creatorcontrib>Zhu, Xiaolu</creatorcontrib><creatorcontrib>Ayres, Fábio J.</creatorcontrib><creatorcontrib>Ells, Anna L.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>ProQuest Nursing and Allied Health Journals</collection><collection>Computer and Information Systems Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>ProQuest Health and Medical</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ProQuest Biological Science Collection</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest Biological Science Journals</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of digital imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rangayyan, Rangaraj M.</au><au>Zhu, Xiaolu</au><au>Ayres, Fábio J.</au><au>Ells, Anna L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Detection of the Optic Nerve Head in Fundus Images of the Retina with Gabor Filters and Phase Portrait Analysis</atitle><jtitle>Journal of digital imaging</jtitle><stitle>J Digit Imaging</stitle><addtitle>J Digit Imaging</addtitle><date>2010-08-01</date><risdate>2010</risdate><volume>23</volume><issue>4</issue><spage>438</spage><epage>453</epage><pages>438-453</pages><issn>0897-1889</issn><eissn>1618-727X</eissn><abstract>We propose a method using Gabor filters and phase portraits to automatically locate the optic nerve head (ONH) in fundus images of the retina. Because the center of the ONH is at or near the focal point of convergence of the retinal vessels, the method includes detection of the vessels using Gabor filters, detection of peaks in the node map obtained via phase portrait analysis, and an intensity-based condition. The method was tested on 40 images from the Digital Retinal Images for Vessel Extraction (DRIVE) database and 81 images from the Structured Analysis of the Retina (STARE) database. An ophthalmologist independently marked the center of the ONH for evaluation of the results. The evaluation of the results includes free-response receiver operating characteristics (FROC) and a measure of distance between the manually marked and detected centers. With the DRIVE database, the centers of the ONH were detected with an average distance of 0.36 mm (18 pixels) to the corresponding centers marked by the ophthalmologist. FROC analysis indicated a sensitivity of 100% at 2.7 false positives per image. With the STARE database, FROC analysis indicated a sensitivity of 88.9% at 4.6 false positives per image.</abstract><cop>New York</cop><pub>Springer-Verlag</pub><pmid>20066466</pmid><doi>10.1007/s10278-009-9261-1</doi><tpages>16</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Algorithms Diagnostic Imaging - methods Fundus Oculi Humans Image Interpretation, Computer-Assisted Imaging Magnetic Resonance Angiography - methods Medicine Medicine & Public Health Micropore Filters Optic Disk - diagnostic imaging Radiography Radiology Retina - diagnostic imaging Retinal Vessels - diagnostic imaging Retinoscopy - methods ROC Curve |
| title | Detection of the Optic Nerve Head in Fundus Images of the Retina with Gabor Filters and Phase Portrait Analysis |
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