{"id":"https://openalex.org/W2102524548","doi":"https://doi.org/10.1109/isbi.2010.5490305","title":"Cardiac segmentation in MR cine data using inverse consistent deformable registration","display_name":"Cardiac segmentation in MR cine data using inverse consistent deformable registration","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W2102524548","doi":"https://doi.org/10.1109/isbi.2010.5490305","mag":"2102524548"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2010.5490305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2010.5490305","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109251531","display_name":"Marie\u2010Pierre Jolly","orcid":null},"institutions":[{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marie-Pierre Jolly","raw_affiliation_strings":["Imaging and Visualization Department, Siemens AG Corporate Research and Development, Princeton, NJ, USA","Siemens Corporate Research, Imaging and Visualization dept., Princeton NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imaging and Visualization Department, Siemens AG Corporate Research and Development, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]},{"raw_affiliation_string":"Siemens Corporate Research, Imaging and Visualization dept., Princeton NJ, USA","institution_ids":["https://openalex.org/I4210137693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060838212","display_name":"Christoph Guetter","orcid":"https://orcid.org/0000-0001-9870-613X"},"institutions":[{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christoph Guetter","raw_affiliation_strings":["Imaging and Visualization Department, Siemens AG Corporate Research and Development, Princeton, NJ, USA","Siemens Corporate Research, Imaging and Visualization dept., Princeton NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imaging and Visualization Department, Siemens AG Corporate Research and Development, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]},{"raw_affiliation_string":"Siemens Corporate Research, Imaging and Visualization dept., Princeton NJ, USA","institution_ids":["https://openalex.org/I4210137693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066274612","display_name":"Jens Guehring","orcid":null},"institutions":[{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jens Guehring","raw_affiliation_strings":["Imaging and Visualization Department, Siemens AG Corporate Research and Development, Princeton, NJ, USA","Siemens Corporate Research, Imaging and Visualization dept., Princeton NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imaging and Visualization Department, Siemens AG Corporate Research and Development, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]},{"raw_affiliation_string":"Siemens Corporate Research, Imaging and Visualization dept., Princeton NJ, USA","institution_ids":["https://openalex.org/I4210137693"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210137693"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"484","last_page":"487"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.7365331053733826},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7106151580810547},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7019010782241821},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6478162407875061},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6408445835113525},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6259133815765381},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5956577062606812},{"id":"https://openalex.org/keywords/deformation","display_name":"Deformation (meteorology)","score":0.5921097993850708},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.5496692061424255},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5456467866897583},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.509711742401123},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.47902339696884155},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.472239226102829},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3635621666908264},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3378923535346985},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24676993489265442},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2229696810245514},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10380852222442627},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08711650967597961}],"concepts":[{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.7365331053733826},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7106151580810547},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7019010782241821},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6478162407875061},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6408445835113525},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6259133815765381},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5956577062606812},{"id":"https://openalex.org/C204366326","wikidata":"https://www.wikidata.org/wiki/Q3027650","display_name":"Deformation (meteorology)","level":2,"score":0.5921097993850708},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.5496692061424255},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5456467866897583},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.509711742401123},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.47902339696884155},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.472239226102829},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3635621666908264},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3378923535346985},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24676993489265442},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2229696810245514},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10380852222442627},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08711650967597961},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2010.5490305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2010.5490305","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1518961746","https://openalex.org/W1525170478","https://openalex.org/W1605601497","https://openalex.org/W1851389655","https://openalex.org/W2045784023","https://openalex.org/W2084669361","https://openalex.org/W2112713547","https://openalex.org/W2124121708","https://openalex.org/W2124632179","https://openalex.org/W2126452566","https://openalex.org/W2158763304","https://openalex.org/W2165680220"],"related_works":["https://openalex.org/W4295532600","https://openalex.org/W2063823869","https://openalex.org/W2047973478","https://openalex.org/W2067569035","https://openalex.org/W4391250048","https://openalex.org/W4313044406","https://openalex.org/W3201505834","https://openalex.org/W4206010360","https://openalex.org/W3110400269","https://openalex.org/W2153667234"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,61],"registration-based":[4],"segmentation":[5],"technique":[6],"to":[7,28,41,48],"fully":[8],"automatically":[9],"segment":[10],"the":[11,43,53,71,85],"left":[12],"ventricle":[13],"in":[14,52],"cardiac":[15,54],"cine":[16],"magnetic":[17],"resonance":[18],"studies.":[19],"We":[20,74],"propose":[21],"an":[22],"inverse":[23],"consistent":[24],"deformable":[25],"registration":[26],"algorithm":[27,64,86],"recover":[29],"one":[30],"set":[31],"of":[32],"forward":[33],"and":[34,65,100],"backward":[35],"deformation":[36,44,72],"fields":[37],"that":[38,84],"allow":[39],"us":[40],"access":[42],"from":[45],"any":[46,49],"frame":[47,51],"other":[50],"sequence.":[55],"Cardiac":[56],"phases":[57],"are":[58],"segmented":[59],"using":[60],"shortest":[62],"path":[63],"time":[66],"consistency":[67],"is":[68],"enforced":[69],"through":[70],"fields.":[73],"demonstrate":[75],"on":[76],"52":[77],"datasets":[78],"with":[79],"expert":[80],"outlined":[81],"ground":[82],"truth":[83],"produces":[87],"accurate":[88],"(1.39":[89],"pixels":[90,94],"median":[91],"error,":[92,96],"2.10":[93],"RMS":[95],"0.88":[97],"Dice":[98],"coefficient)":[99],"fast":[101],"(0.3":[102],"s/image)":[103],"results.":[104]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}