Brachytherapy Seed Localization Using Geometric and Linear Programming Techniques
We propose an optimization algorithm to solve the brachytherapy seed localization problem in prostate brachytherapy. Our algorithm is based on novel geometric approaches to exploit the special structure of the problem and relies on a number of key observations which help us formulate the optimizatio...
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| Veröffentlicht in: | IEEE transactions on medical imaging 2007-09, Vol.26 (9), p.1291-1304 |
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| container_title | IEEE transactions on medical imaging |
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| creator | Singh, V. Mukherjee, L. Jinhui Xu Hoffmann, K.R. Dinu, P.M. Podgorsak, M. |
| description | We propose an optimization algorithm to solve the brachytherapy seed localization problem in prostate brachytherapy. Our algorithm is based on novel geometric approaches to exploit the special structure of the problem and relies on a number of key observations which help us formulate the optimization problem as a minimization integer program (IP). Our IP model precisely defines the feasibility polyhedron for this problem using a polynomial number of half-spaces; the solution to its corresponding linear program is rounded to yield an integral solution to our task of determining correspondences between seeds in multiple projection images. The algorithm is efficient in theory as well as in practice and performs well on simulation data (~98% accuracy) and real X-ray images (~95% accuracy). We present in detail the underlying ideas and an extensive set of performance evaluations based on our implementation. |
| doi_str_mv | 10.1109/TMI.2007.900740 |
| format | Article |
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Our algorithm is based on novel geometric approaches to exploit the special structure of the problem and relies on a number of key observations which help us formulate the optimization problem as a minimization integer program (IP). Our IP model precisely defines the feasibility polyhedron for this problem using a polynomial number of half-spaces; the solution to its corresponding linear program is rounded to yield an integral solution to our task of determining correspondences between seeds in multiple projection images. The algorithm is efficient in theory as well as in practice and performs well on simulation data (~98% accuracy) and real X-ray images (~95% accuracy). We present in detail the underlying ideas and an extensive set of performance evaluations based on our implementation.</description><identifier>ISSN: 0278-0062</identifier><identifier>EISSN: 1558-254X</identifier><identifier>DOI: 10.1109/TMI.2007.900740</identifier><identifier>PMID: 17896600</identifier><identifier>CODEN: ITMID4</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Accuracy ; Algorithms ; Artificial Intelligence ; Brachytherapy ; Brachytherapy - instrumentation ; Brachytherapy - methods ; Brachytherapy seed localization (BSL) ; Cancer ; Computer science ; geometric optimization ; Humans ; Imaging, Three-Dimensional - methods ; Implants ; Information Storage and Retrieval - methods ; integer programming ; Linear programming ; Localization ; Male ; Mathematical models ; Medical treatment ; Minimization methods ; multiview point correspondence ; Neoplasms ; Optimization ; Pattern Recognition, Automated - methods ; Polynomials ; Position (location) ; Programming, Linear ; Prostatic Neoplasms - diagnostic imaging ; Prostatic Neoplasms - radiotherapy ; Prosthesis Implantation - methods ; Radiographic Image Enhancement - methods ; Radiographic Image Interpretation, Computer-Assisted - methods ; Radiotherapy, Computer-Assisted - methods ; Reproducibility of Results ; Seeds ; Sensitivity and Specificity ; X-ray imaging</subject><ispartof>IEEE transactions on medical imaging, 2007-09, Vol.26 (9), p.1291-1304</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2007</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c354t-6bc39a03f0660d9afe5dd6652f057cf4a114dd05a81b40121233685b0205def13</citedby><cites>FETCH-LOGICAL-c354t-6bc39a03f0660d9afe5dd6652f057cf4a114dd05a81b40121233685b0205def13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4298156$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4298156$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/17896600$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Singh, V.</creatorcontrib><creatorcontrib>Mukherjee, L.</creatorcontrib><creatorcontrib>Jinhui Xu</creatorcontrib><creatorcontrib>Hoffmann, K.R.</creatorcontrib><creatorcontrib>Dinu, P.M.</creatorcontrib><creatorcontrib>Podgorsak, M.</creatorcontrib><title>Brachytherapy Seed Localization Using Geometric and Linear Programming Techniques</title><title>IEEE transactions on medical imaging</title><addtitle>TMI</addtitle><addtitle>IEEE Trans Med Imaging</addtitle><description>We propose an optimization algorithm to solve the brachytherapy seed localization problem in prostate brachytherapy. Our algorithm is based on novel geometric approaches to exploit the special structure of the problem and relies on a number of key observations which help us formulate the optimization problem as a minimization integer program (IP). Our IP model precisely defines the feasibility polyhedron for this problem using a polynomial number of half-spaces; the solution to its corresponding linear program is rounded to yield an integral solution to our task of determining correspondences between seeds in multiple projection images. The algorithm is efficient in theory as well as in practice and performs well on simulation data (~98% accuracy) and real X-ray images (~95% accuracy). We present in detail the underlying ideas and an extensive set of performance evaluations based on our implementation.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Artificial Intelligence</subject><subject>Brachytherapy</subject><subject>Brachytherapy - instrumentation</subject><subject>Brachytherapy - methods</subject><subject>Brachytherapy seed localization (BSL)</subject><subject>Cancer</subject><subject>Computer science</subject><subject>geometric optimization</subject><subject>Humans</subject><subject>Imaging, Three-Dimensional - methods</subject><subject>Implants</subject><subject>Information Storage and Retrieval - methods</subject><subject>integer programming</subject><subject>Linear programming</subject><subject>Localization</subject><subject>Male</subject><subject>Mathematical models</subject><subject>Medical treatment</subject><subject>Minimization methods</subject><subject>multiview point correspondence</subject><subject>Neoplasms</subject><subject>Optimization</subject><subject>Pattern Recognition, Automated - methods</subject><subject>Polynomials</subject><subject>Position (location)</subject><subject>Programming, Linear</subject><subject>Prostatic Neoplasms - diagnostic imaging</subject><subject>Prostatic Neoplasms - radiotherapy</subject><subject>Prosthesis Implantation - methods</subject><subject>Radiographic Image Enhancement - methods</subject><subject>Radiographic Image Interpretation, Computer-Assisted - methods</subject><subject>Radiotherapy, Computer-Assisted - methods</subject><subject>Reproducibility of Results</subject><subject>Seeds</subject><subject>Sensitivity and Specificity</subject><subject>X-ray imaging</subject><issn>0278-0062</issn><issn>1558-254X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><sourceid>EIF</sourceid><recordid>eNqF0c1v0zAYBnALMbEyOHNAQhEHxCXd-_or9hEmGJM6AaKTuEWu82b11CSdnR7KX4-jViDtsF3sg39-_PEw9gZhjgj2fHl9NecA1dzmQcIzNkOlTMmV_P2czYBXpgTQ_JS9TOkOAKUC-4KdYmWs1gAz9vNzdH69H9cU3XZf_CJqisXg3Sb8cWMY-uImhf62uKShozEGX7g-g9CTi8WPONxG13UTWJJf9-F-R-kVO2ndJtHr43zGbr5-WV58KxffL68uPi1KL5QcS73ywjoQLeSLNNa1pJpGa8VbUJVvpUOUTQPKGVxJQI5cCG3UCjiohloUZ-zDIXcbh-ncse5C8rTZuJ6GXaq1EWgrLZ-EaCVaYSf48XGoK5RcWNBP03xNIw2oKfX9A3o37GKfv6Y2WoLKTxYZnR-Qj0NKkdp6G0Pn4j4n1VPTdW66npquD03nHe-OsbtVR81_f6w2g7cHEIjo37Lk1qDS4i9Vn6ov</recordid><startdate>200709</startdate><enddate>200709</enddate><creator>Singh, V.</creator><creator>Mukherjee, L.</creator><creator>Jinhui Xu</creator><creator>Hoffmann, K.R.</creator><creator>Dinu, P.M.</creator><creator>Podgorsak, M.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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instrumentation</topic><topic>Brachytherapy - methods</topic><topic>Brachytherapy seed localization (BSL)</topic><topic>Cancer</topic><topic>Computer science</topic><topic>geometric optimization</topic><topic>Humans</topic><topic>Imaging, Three-Dimensional - methods</topic><topic>Implants</topic><topic>Information Storage and Retrieval - methods</topic><topic>integer programming</topic><topic>Linear programming</topic><topic>Localization</topic><topic>Male</topic><topic>Mathematical models</topic><topic>Medical treatment</topic><topic>Minimization methods</topic><topic>multiview point correspondence</topic><topic>Neoplasms</topic><topic>Optimization</topic><topic>Pattern Recognition, Automated - methods</topic><topic>Polynomials</topic><topic>Position (location)</topic><topic>Programming, Linear</topic><topic>Prostatic Neoplasms - diagnostic imaging</topic><topic>Prostatic Neoplasms - radiotherapy</topic><topic>Prosthesis Implantation - methods</topic><topic>Radiographic Image Enhancement - 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Academic</collection><jtitle>IEEE transactions on medical imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Singh, V.</au><au>Mukherjee, L.</au><au>Jinhui Xu</au><au>Hoffmann, K.R.</au><au>Dinu, P.M.</au><au>Podgorsak, M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Brachytherapy Seed Localization Using Geometric and Linear Programming Techniques</atitle><jtitle>IEEE transactions on medical imaging</jtitle><stitle>TMI</stitle><addtitle>IEEE Trans Med Imaging</addtitle><date>2007-09</date><risdate>2007</risdate><volume>26</volume><issue>9</issue><spage>1291</spage><epage>1304</epage><pages>1291-1304</pages><issn>0278-0062</issn><eissn>1558-254X</eissn><coden>ITMID4</coden><abstract>We propose an optimization algorithm to solve the brachytherapy seed localization problem in prostate brachytherapy. 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| subjects | Accuracy Algorithms Artificial Intelligence Brachytherapy Brachytherapy - instrumentation Brachytherapy - methods Brachytherapy seed localization (BSL) Cancer Computer science geometric optimization Humans Imaging, Three-Dimensional - methods Implants Information Storage and Retrieval - methods integer programming Linear programming Localization Male Mathematical models Medical treatment Minimization methods multiview point correspondence Neoplasms Optimization Pattern Recognition, Automated - methods Polynomials Position (location) Programming, Linear Prostatic Neoplasms - diagnostic imaging Prostatic Neoplasms - radiotherapy Prosthesis Implantation - methods Radiographic Image Enhancement - methods Radiographic Image Interpretation, Computer-Assisted - methods Radiotherapy, Computer-Assisted - methods Reproducibility of Results Seeds Sensitivity and Specificity X-ray imaging |
| title | Brachytherapy Seed Localization Using Geometric and Linear Programming Techniques |
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