{"id":"https://openalex.org/W3010683841","doi":"https://doi.org/10.1117/12.2550535","title":"The image-to-physical liver registration sparse data challenge: characterizing inverse biomechanical model resolution","display_name":"The image-to-physical liver registration sparse data challenge: characterizing inverse biomechanical model resolution","publication_year":2020,"publication_date":"2020-03-16","ids":{"openalex":"https://openalex.org/W3010683841","doi":"https://doi.org/10.1117/12.2550535","mag":"3010683841"},"language":"en","primary_location":{"id":"doi:10.1117/12.2550535","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2550535","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling","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/A5036452971","display_name":"Jon S. Heiselman","orcid":"https://orcid.org/0000-0002-4414-8846"},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jon S. Heiselman","raw_affiliation_strings":["Vanderbilt Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Vanderbilt Univ. (United States)","institution_ids":["https://openalex.org/I200719446"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036352350","display_name":"Michael I. Miga","orcid":"https://orcid.org/0000-0002-0694-9765"},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael I. Miga","raw_affiliation_strings":["Vanderbilt Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Vanderbilt Univ. (United States)","institution_ids":["https://openalex.org/I200719446"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I200719446"],"apc_list":null,"apc_paid":null,"fwci":0.0854,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.27577445,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"50","last_page":"50"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9962000250816345,"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"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9962000250816345,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.982699990272522,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9811999797821045,"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/image-registration","display_name":"Image registration","score":0.7768144607543945},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6560514569282532},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5755251049995422},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5344409346580505},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.488262414932251},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.46912881731987},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.4573372006416321},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.45730072259902954},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.45037615299224854},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.4423040747642517},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14541056752204895}],"concepts":[{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.7768144607543945},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6560514569282532},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5755251049995422},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5344409346580505},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.488262414932251},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.46912881731987},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.4573372006416321},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.45730072259902954},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.45037615299224854},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.4423040747642517},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14541056752204895},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2550535","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2550535","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2588069848","https://openalex.org/W2921710305","https://openalex.org/W2999095562"],"related_works":["https://openalex.org/W4317939968","https://openalex.org/W2014452451","https://openalex.org/W3037497593","https://openalex.org/W2118640186","https://openalex.org/W2331917905","https://openalex.org/W3155039083","https://openalex.org/W2471562626","https://openalex.org/W2461863667","https://openalex.org/W2295804706","https://openalex.org/W3168515805"],"abstract_inverted_index":{"Image-guided":[0],"liver":[1,27,74,93],"surgery":[2],"relies":[3],"on":[4,90],"intraoperatively":[5],"acquired":[6],"data":[7,23,42,77,87,139,208,230,235],"to":[8,39,69,110,137,144,167,213],"create":[9],"an":[10,130,218],"accurate":[11,37],"alignment":[12],"between":[13],"image":[14],"space":[15],"and":[16,100,113,184,201,252],"the":[17,25,96,106,123,159,168,189,205,229,233,249],"physical":[18],"patient":[19],"anatomy.":[20],"Often,":[21],"sparse":[22,40,76,86,138,207,234],"of":[24,84,98,115,163,182,228],"anterior":[26],"surface":[28,41],"can":[29],"be":[30,70],"collected":[31,89],"for":[32,63,95,122,134,196],"these":[33,116],"registrations.":[34],"However,":[35],"achieving":[36],"registration":[38,75,103,124,136,148],"when":[43],"soft":[44],"tissue":[45],"deformation":[46],"is":[47,108,151,237],"present":[48],"remains":[49],"a":[50,60,80,91,119,154,179],"challenging":[51],"open":[52],"problem.":[53],"While":[54],"many":[55],"approaches":[56],"have":[57],"been":[58],"developed,":[59],"common":[61],"standard":[62],"comparing":[64,101],"algorithm":[65],"performance":[66],"has":[67],"yet":[68],"adopted.":[71],"The":[72,226],"image-to-physical":[73],"challenge":[78,107,128,190,209,236,250],"offers":[79],"publicly":[81],"available":[82],"dataset":[83],"realistic":[85],"patterns":[88],"deforming":[92],"phantom":[94],"purpose":[97],"evaluating":[99],"potential":[102],"approaches.":[104],"Additionally,":[105],"designed":[109],"allow":[111],"testing":[112],"characterization":[114],"methods":[117],"as":[118],"general":[120],"utility":[121],"community.":[125],"Using":[126],"this":[127,171,173],"environment,":[129],"inverse":[131],"biomechanical":[132],"method":[133],"deformable":[135],"was":[140,176,186,199,211,241],"investigated":[141],"with":[142],"respect":[143],"how":[145],"whole-organ":[146],"target":[147],"error":[149],"(TRE)":[150],"impacted":[152],"by":[153,232,248],"model":[155,197],"parameter":[156,175,194],"that":[157],"controls":[158],"spatial":[160],"reconstructive":[161],"resolution":[162,174,198],"mechanical":[164],"loads":[165],"applied":[166],"organ.":[169],"For":[170],"analysis,":[172],"varied":[177],"across":[178,204],"wide":[180],"range":[181],"values":[183],"TRE":[185,203],"calculated":[187],"from":[188],"dataset.":[191],"An":[192],"optimal":[193],"value":[195,227],"found":[200],"average":[202],"112":[206],"cases":[210],"reduced":[212],"3.08":[214],"±":[215],"0.85":[216],"mm,":[217],"approximate":[219],"32%":[220],"improvement":[221],"over":[222],"previously":[223],"reported":[224],"results.":[225],"offered":[231],"evident.":[238],"This":[239],"work":[240],"performed":[242],"entirely":[243],"using":[244],"information":[245],"automatically":[246],"generated":[247],"submission":[251],"processing":[253],"site.":[254]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}