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Surface normal overlap: a computer-aided detection algorithm with application to colonic polyps and lung nodules in helical CT
We developed a novel computer-aided detection (CAD) algorithm called the surface normal overlap method that we applied to colonic polyp detection and lung nodule detection in helical computed tomography (CT) images. We demonstrate some of the theoretical aspects of this algorithm using a statistical...
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| Published in: | IEEE transactions on medical imaging 2004-06, Vol.23 (6), p.661-675 |
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| Main Authors: | , , , , , , , |
| Format: | Article |
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| cited_by | cdi_FETCH-LOGICAL-c434t-9af207a855980d862d7ffb33152e15d7d96d7a184018ed8f000464c046033a83 |
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| cites | cdi_FETCH-LOGICAL-c434t-9af207a855980d862d7ffb33152e15d7d96d7a184018ed8f000464c046033a83 |
| container_end_page | 675 |
| container_issue | 6 |
| container_start_page | 661 |
| container_title | IEEE transactions on medical imaging |
| container_volume | 23 |
| creator | Paik, D.S. Beaulieu, C.F. Rubin, G.D. Acar, B. Jeffrey, R.B. Yee, J. Dey, J. Napel, S. |
| description | We developed a novel computer-aided detection (CAD) algorithm called the surface normal overlap method that we applied to colonic polyp detection and lung nodule detection in helical computed tomography (CT) images. We demonstrate some of the theoretical aspects of this algorithm using a statistical shape model. The algorithm was then optimized on simulated CT data and evaluated using a per-lesion cross-validation on 8 CT colonography datasets and on 8 chest CT datasets. It is able to achieve 100% sensitivity for colonic polyps 10 mm and larger at 7.0 false positives (FPs)/dataset and 90% sensitivity for solid lung nodules 6 mm and larger at 5.6 FP/dataset. |
| doi_str_mv | 10.1109/TMI.2004.826362 |
| format | article |
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We demonstrate some of the theoretical aspects of this algorithm using a statistical shape model. The algorithm was then optimized on simulated CT data and evaluated using a per-lesion cross-validation on 8 CT colonography datasets and on 8 chest CT datasets. It is able to achieve 100% sensitivity for colonic polyps 10 mm and larger at 7.0 false positives (FPs)/dataset and 90% sensitivity for solid lung nodules 6 mm and larger at 5.6 FP/dataset.</description><identifier>ISSN: 0278-0062</identifier><identifier>EISSN: 1558-254X</identifier><identifier>DOI: 10.1109/TMI.2004.826362</identifier><identifier>PMID: 15191141</identifier><identifier>CODEN: ITMID4</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Algorithms ; Application software ; Attenuation ; Cancer ; Colonic polyps ; Colonic Polyps - diagnostic imaging ; Computed tomography ; Databases, Factual ; Detection algorithms ; Humans ; Imaging, Three-Dimensional - methods ; Lungs ; Pattern Recognition, Automated ; Phantoms, Imaging ; Radiographic Image Interpretation, Computer-Assisted - methods ; Radiology ; Reproducibility of Results ; Retrospective Studies ; Sensitivity and Specificity ; Shape ; Single-Blind Method ; Solitary Pulmonary Nodule - diagnostic imaging ; Tomography, Spiral Computed - methods ; Virtual colonoscopy</subject><ispartof>IEEE transactions on medical imaging, 2004-06, Vol.23 (6), p.661-675</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2004</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c434t-9af207a855980d862d7ffb33152e15d7d96d7a184018ed8f000464c046033a83</citedby><cites>FETCH-LOGICAL-c434t-9af207a855980d862d7ffb33152e15d7d96d7a184018ed8f000464c046033a83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1302205$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,54796</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15191141$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Paik, D.S.</creatorcontrib><creatorcontrib>Beaulieu, C.F.</creatorcontrib><creatorcontrib>Rubin, G.D.</creatorcontrib><creatorcontrib>Acar, B.</creatorcontrib><creatorcontrib>Jeffrey, R.B.</creatorcontrib><creatorcontrib>Yee, J.</creatorcontrib><creatorcontrib>Dey, J.</creatorcontrib><creatorcontrib>Napel, S.</creatorcontrib><title>Surface normal overlap: a computer-aided detection algorithm with application to colonic polyps and lung nodules in helical CT</title><title>IEEE transactions on medical imaging</title><addtitle>TMI</addtitle><addtitle>IEEE Trans Med Imaging</addtitle><description>We developed a novel computer-aided detection (CAD) algorithm called the surface normal overlap method that we applied to colonic polyp detection and lung nodule detection in helical computed tomography (CT) images. 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It is able to achieve 100% sensitivity for colonic polyps 10 mm and larger at 7.0 false positives (FPs)/dataset and 90% sensitivity for solid lung nodules 6 mm and larger at 5.6 FP/dataset.</description><subject>Algorithms</subject><subject>Application software</subject><subject>Attenuation</subject><subject>Cancer</subject><subject>Colonic polyps</subject><subject>Colonic Polyps - diagnostic imaging</subject><subject>Computed tomography</subject><subject>Databases, Factual</subject><subject>Detection algorithms</subject><subject>Humans</subject><subject>Imaging, Three-Dimensional - methods</subject><subject>Lungs</subject><subject>Pattern Recognition, Automated</subject><subject>Phantoms, Imaging</subject><subject>Radiographic Image Interpretation, Computer-Assisted - methods</subject><subject>Radiology</subject><subject>Reproducibility of Results</subject><subject>Retrospective Studies</subject><subject>Sensitivity and Specificity</subject><subject>Shape</subject><subject>Single-Blind Method</subject><subject>Solitary Pulmonary Nodule - diagnostic imaging</subject><subject>Tomography, Spiral Computed - methods</subject><subject>Virtual colonoscopy</subject><issn>0278-0062</issn><issn>1558-254X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><recordid>eNqFks1v1DAQxS0EokvhzAEJWRzglO2MHTtOb2jFR6UiDuyBW-TGkzaVEwc7AfXC347DrlSJA73MHOb3ZkZPj7GXCFtEqM_2Xy62AqDcGqGlFo_YBpUyhVDl98dsA6IyBYAWJ-xZSrcAWCqon7ITVFgjlrhhv78tsbMt8THEwXoeflL0djrnlrdhmJaZYmF7R447mqmd-zBy669D7Oebgf_Kldtp8n1r_47mkGU-jH3Lp-DvpsTt6Lhfxut8wC2eEu9HfkOrwPPd_jl70lmf6MWxn7L9xw_73efi8uuni937y6ItZTkXte0EVNYoVRtwRgtXdd2VlKgEoXKVq7WrLJoS0JAzHWRLdNnmAlJaI0_Zu8PaKYYfC6W5GfrUkvd2pLCkxhgJWGu1km__S1YCUK1mPwQKoxFEvv8QiJWoQekyg2_-AW_DEsdsy_pfDZWWKkNnB6iNIaVIXTPFfrDxrkFo1kg0ORLNGonmEImseH1cu1wN5O75YwYy8OoA9ER0P5YgBCj5B4rWuT0</recordid><startdate>20040601</startdate><enddate>20040601</enddate><creator>Paik, D.S.</creator><creator>Beaulieu, C.F.</creator><creator>Rubin, G.D.</creator><creator>Acar, B.</creator><creator>Jeffrey, R.B.</creator><creator>Yee, J.</creator><creator>Dey, J.</creator><creator>Napel, S.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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diagnostic imaging</topic><topic>Computed tomography</topic><topic>Databases, Factual</topic><topic>Detection algorithms</topic><topic>Humans</topic><topic>Imaging, Three-Dimensional - methods</topic><topic>Lungs</topic><topic>Pattern Recognition, Automated</topic><topic>Phantoms, Imaging</topic><topic>Radiographic Image Interpretation, Computer-Assisted - methods</topic><topic>Radiology</topic><topic>Reproducibility of Results</topic><topic>Retrospective Studies</topic><topic>Sensitivity and Specificity</topic><topic>Shape</topic><topic>Single-Blind Method</topic><topic>Solitary Pulmonary Nodule - diagnostic imaging</topic><topic>Tomography, Spiral Computed - methods</topic><topic>Virtual colonoscopy</topic><toplevel>online_resources</toplevel><creatorcontrib>Paik, D.S.</creatorcontrib><creatorcontrib>Beaulieu, C.F.</creatorcontrib><creatorcontrib>Rubin, G.D.</creatorcontrib><creatorcontrib>Acar, B.</creatorcontrib><creatorcontrib>Jeffrey, R.B.</creatorcontrib><creatorcontrib>Yee, J.</creatorcontrib><creatorcontrib>Dey, J.</creatorcontrib><creatorcontrib>Napel, S.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library Online</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>IEEE transactions on medical imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Paik, D.S.</au><au>Beaulieu, C.F.</au><au>Rubin, G.D.</au><au>Acar, B.</au><au>Jeffrey, R.B.</au><au>Yee, J.</au><au>Dey, J.</au><au>Napel, S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Surface normal overlap: a computer-aided detection algorithm with application to colonic polyps and lung nodules in helical CT</atitle><jtitle>IEEE transactions on medical imaging</jtitle><stitle>TMI</stitle><addtitle>IEEE Trans Med Imaging</addtitle><date>2004-06-01</date><risdate>2004</risdate><volume>23</volume><issue>6</issue><spage>661</spage><epage>675</epage><pages>661-675</pages><issn>0278-0062</issn><eissn>1558-254X</eissn><coden>ITMID4</coden><abstract>We developed a novel computer-aided detection (CAD) algorithm called the surface normal overlap method that we applied to colonic polyp detection and lung nodule detection in helical computed tomography (CT) images. We demonstrate some of the theoretical aspects of this algorithm using a statistical shape model. The algorithm was then optimized on simulated CT data and evaluated using a per-lesion cross-validation on 8 CT colonography datasets and on 8 chest CT datasets. It is able to achieve 100% sensitivity for colonic polyps 10 mm and larger at 7.0 false positives (FPs)/dataset and 90% sensitivity for solid lung nodules 6 mm and larger at 5.6 FP/dataset.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>15191141</pmid><doi>10.1109/TMI.2004.826362</doi><tpages>15</tpages></addata></record> |
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| ispartof | IEEE transactions on medical imaging, 2004-06, Vol.23 (6), p.661-675 |
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| language | eng |
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| source | IEEE Xplore (Online service) |
| subjects | Algorithms Application software Attenuation Cancer Colonic polyps Colonic Polyps - diagnostic imaging Computed tomography Databases, Factual Detection algorithms Humans Imaging, Three-Dimensional - methods Lungs Pattern Recognition, Automated Phantoms, Imaging Radiographic Image Interpretation, Computer-Assisted - methods Radiology Reproducibility of Results Retrospective Studies Sensitivity and Specificity Shape Single-Blind Method Solitary Pulmonary Nodule - diagnostic imaging Tomography, Spiral Computed - methods Virtual colonoscopy |
| title | Surface normal overlap: a computer-aided detection algorithm with application to colonic polyps and lung nodules in helical CT |
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