An iterative point correspondence algorithm for automatic image registration: An application to dental subtraction radiography
Abstract In this paper, an Automatic Iterative Point Correspondence (AIPC) algorithm towards image registration is presented. Given an image pair, distinctive points are extracted only in one of the images (reference image), and the corresponding points in the other image are obtained automatically...
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| Veröffentlicht in: | Computer methods and programs in biomedicine 2009-01, Vol.93 (1), p.61-72 |
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| container_title | Computer methods and programs in biomedicine |
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| creator | Markaki, Vasiliki E Asvestas, Pantelis A Matsopoulos, George K |
| description | Abstract In this paper, an Automatic Iterative Point Correspondence (AIPC) algorithm towards image registration is presented. Given an image pair, distinctive points are extracted only in one of the images (reference image), and the corresponding points in the other image are obtained automatically by maximizing a similarity measure between regions of the two images with respect to the parameters of a local transformation. The maximization is accomplished by means of an iterative procedure, in which candidate solutions for the transformation parameters are tested at each iteration; these solutions are evaluated by the similarity measure between image regions. The detected point pairs by the application of the AIPC algorithm are then used to estimate the parameters of a global projective transformation for the registration of the image pair. The proposed AIPC algorithm was applied on 113 in vitro and in vivo dental image pairs providing improved registration accuracy against three widely used registration methods. |
| doi_str_mv | 10.1016/j.cmpb.2008.07.003 |
| format | Article |
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Given an image pair, distinctive points are extracted only in one of the images (reference image), and the corresponding points in the other image are obtained automatically by maximizing a similarity measure between regions of the two images with respect to the parameters of a local transformation. The maximization is accomplished by means of an iterative procedure, in which candidate solutions for the transformation parameters are tested at each iteration; these solutions are evaluated by the similarity measure between image regions. The detected point pairs by the application of the AIPC algorithm are then used to estimate the parameters of a global projective transformation for the registration of the image pair. The proposed AIPC algorithm was applied on 113 in vitro and in vivo dental image pairs providing improved registration accuracy against three widely used registration methods.</description><identifier>ISSN: 0169-2607</identifier><identifier>EISSN: 1872-7565</identifier><identifier>DOI: 10.1016/j.cmpb.2008.07.003</identifier><identifier>PMID: 18760858</identifier><language>eng</language><publisher>Ireland: Elsevier Ireland Ltd</publisher><subject>Algorithms ; Automatic point correspondence ; Biometry ; Dental Models ; Dental subtraction radiography ; Humans ; Internal Medicine ; Iterative Closest Point ; Mutual information ; Other ; Point-based registration ; Radiographic Image Interpretation, Computer-Assisted ; Radiography, Dental, Digital - statistics & numerical data ; Template matching</subject><ispartof>Computer methods and programs in biomedicine, 2009-01, Vol.93 (1), p.61-72</ispartof><rights>Elsevier Ireland Ltd</rights><rights>2008 Elsevier Ireland Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c440t-6626dea42e61987f0f86c68f4f9e88af309e6b694f2f597066fa36ea469d14393</citedby><cites>FETCH-LOGICAL-c440t-6626dea42e61987f0f86c68f4f9e88af309e6b694f2f597066fa36ea469d14393</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0169260708001788$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3536,27903,27904,65309</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18760858$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Markaki, Vasiliki E</creatorcontrib><creatorcontrib>Asvestas, Pantelis A</creatorcontrib><creatorcontrib>Matsopoulos, George K</creatorcontrib><title>An iterative point correspondence algorithm for automatic image registration: An application to dental subtraction radiography</title><title>Computer methods and programs in biomedicine</title><addtitle>Comput Methods Programs Biomed</addtitle><description>Abstract In this paper, an Automatic Iterative Point Correspondence (AIPC) algorithm towards image registration is presented. Given an image pair, distinctive points are extracted only in one of the images (reference image), and the corresponding points in the other image are obtained automatically by maximizing a similarity measure between regions of the two images with respect to the parameters of a local transformation. The maximization is accomplished by means of an iterative procedure, in which candidate solutions for the transformation parameters are tested at each iteration; these solutions are evaluated by the similarity measure between image regions. The detected point pairs by the application of the AIPC algorithm are then used to estimate the parameters of a global projective transformation for the registration of the image pair. The proposed AIPC algorithm was applied on 113 in vitro and in vivo dental image pairs providing improved registration accuracy against three widely used registration methods.</description><subject>Algorithms</subject><subject>Automatic point correspondence</subject><subject>Biometry</subject><subject>Dental Models</subject><subject>Dental subtraction radiography</subject><subject>Humans</subject><subject>Internal Medicine</subject><subject>Iterative Closest Point</subject><subject>Mutual information</subject><subject>Other</subject><subject>Point-based registration</subject><subject>Radiographic Image Interpretation, Computer-Assisted</subject><subject>Radiography, Dental, Digital - statistics & numerical data</subject><subject>Template matching</subject><issn>0169-2607</issn><issn>1872-7565</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkkGL1DAUx4Mo7uzqF_AgOXlrfUnbNBURlmVXhQUP6jlk0pfZjG1Tk3RhLn5205kBwYOewgu____wfo-QVwxKBky83ZdmnLclB5AltCVA9YRsmGx50TaieUo2GeoKLqC9IJcx7gGAN414Ti4yJEA2ckN-XU_UJQw6uUeks3dTosaHgHH2U4-TQaqHnQ8uPYzU-kD1kvyYaUPdqHdIA-5cTGveT-9obtPzPDhznGnyNHckPdC4bDNkjr9B987vgp4fDi_IM6uHiC_P7xX5fnf77eZTcf_l4-eb6_vC1DWkQgguetQ1R8E62VqwUhghbW07lFLbCjoUW9HVltuma0EIqyuRA6LrWV111RV5c-qdg_-5YExqdNHgMOgJ_RKVEBJkDdV_QQ6VFFyyDPITaIKPMaBVc8gbCQfFQK161F6tetSqR0Gr4Nj--ty-bEfs_0TOPjLw_gRgXsajw6CicauF3gU0SfXe_bv_w19xM7gp2xh-4AHj3i9hymtWTEWuQH1dD2S9D5AArJWy-g1_aLh4</recordid><startdate>20090101</startdate><enddate>20090101</enddate><creator>Markaki, Vasiliki E</creator><creator>Asvestas, Pantelis A</creator><creator>Matsopoulos, George K</creator><general>Elsevier Ireland Ltd</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>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>20090101</creationdate><title>An iterative point correspondence algorithm for automatic image registration: An application to dental subtraction radiography</title><author>Markaki, Vasiliki E ; Asvestas, Pantelis A ; Matsopoulos, George K</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c440t-6626dea42e61987f0f86c68f4f9e88af309e6b694f2f597066fa36ea469d14393</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Algorithms</topic><topic>Automatic point correspondence</topic><topic>Biometry</topic><topic>Dental Models</topic><topic>Dental subtraction radiography</topic><topic>Humans</topic><topic>Internal Medicine</topic><topic>Iterative Closest Point</topic><topic>Mutual information</topic><topic>Other</topic><topic>Point-based registration</topic><topic>Radiographic Image Interpretation, Computer-Assisted</topic><topic>Radiography, Dental, Digital - statistics & numerical data</topic><topic>Template matching</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Markaki, Vasiliki E</creatorcontrib><creatorcontrib>Asvestas, Pantelis A</creatorcontrib><creatorcontrib>Matsopoulos, George K</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Computer methods and programs in biomedicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Markaki, Vasiliki E</au><au>Asvestas, Pantelis A</au><au>Matsopoulos, George K</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An iterative point correspondence algorithm for automatic image registration: An application to dental subtraction radiography</atitle><jtitle>Computer methods and programs in biomedicine</jtitle><addtitle>Comput Methods Programs Biomed</addtitle><date>2009-01-01</date><risdate>2009</risdate><volume>93</volume><issue>1</issue><spage>61</spage><epage>72</epage><pages>61-72</pages><issn>0169-2607</issn><eissn>1872-7565</eissn><abstract>Abstract In this paper, an Automatic Iterative Point Correspondence (AIPC) algorithm towards image registration is presented. Given an image pair, distinctive points are extracted only in one of the images (reference image), and the corresponding points in the other image are obtained automatically by maximizing a similarity measure between regions of the two images with respect to the parameters of a local transformation. The maximization is accomplished by means of an iterative procedure, in which candidate solutions for the transformation parameters are tested at each iteration; these solutions are evaluated by the similarity measure between image regions. The detected point pairs by the application of the AIPC algorithm are then used to estimate the parameters of a global projective transformation for the registration of the image pair. 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| ispartof | Computer methods and programs in biomedicine, 2009-01, Vol.93 (1), p.61-72 |
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| language | eng |
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| source | MEDLINE; Elsevier ScienceDirect Journals |
| subjects | Algorithms Automatic point correspondence Biometry Dental Models Dental subtraction radiography Humans Internal Medicine Iterative Closest Point Mutual information Other Point-based registration Radiographic Image Interpretation, Computer-Assisted Radiography, Dental, Digital - statistics & numerical data Template matching |
| title | An iterative point correspondence algorithm for automatic image registration: An application to dental subtraction radiography |
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