{"id":"https://openalex.org/W2088366205","doi":"https://doi.org/10.1145/2461217.2461239","title":"3D reconstruction from CT-scan volume dataset application to kidney modeling","display_name":"3D reconstruction from CT-scan volume dataset application to kidney modeling","publication_year":2011,"publication_date":"2011-04-28","ids":{"openalex":"https://openalex.org/W2088366205","doi":"https://doi.org/10.1145/2461217.2461239","mag":"2088366205"},"language":"en","primary_location":{"id":"doi:10.1145/2461217.2461239","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2461217.2461239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th Spring Conference on Computer Graphics","raw_type":"proceedings-article"},"type":"preprint","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/A5086034332","display_name":"Valentin Leonardi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Valentin Leonardi","raw_affiliation_strings":["Universit\u00e9 de la M\u00e9diterran\u00e9e (Aix-Marseille 2), LSIS, UMR CNRS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 de la M\u00e9diterran\u00e9e (Aix-Marseille 2), LSIS, UMR CNRS","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077797776","display_name":"Vincent Vidal","orcid":"https://orcid.org/0000-0003-1680-3986"},"institutions":[{"id":"https://openalex.org/I21491767","display_name":"Aix-Marseille Universit\u00e9","ror":"https://ror.org/035xkbk20","country_code":"FR","type":"education","lineage":["https://openalex.org/I21491767"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Vincent Vidal","raw_affiliation_strings":["Universit\u00e9 de le M\u00e9diterran\u00e9e (Aix-Marseille 2), EA, CERIMED"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 de le M\u00e9diterran\u00e9e (Aix-Marseille 2), EA, CERIMED","institution_ids":["https://openalex.org/I21491767"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071749162","display_name":"Jean\u2010Luc Mari","orcid":"https://orcid.org/0000-0002-9552-6739"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jean-Luc Mari","raw_affiliation_strings":["Universit\u00e9 de la M\u00e9diterran\u00e9e (Aix-Marseille 2), LSIS, UMR CNRS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 de la M\u00e9diterran\u00e9e (Aix-Marseille 2), LSIS, UMR CNRS","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108302108","display_name":"Marc Daniel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marc Daniel","raw_affiliation_strings":["Universit\u00e9 de la M\u00e9diterran\u00e9e (Aix-Marseille 2), LSIS, UMR CNRS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 de la M\u00e9diterran\u00e9e (Aix-Marseille 2), LSIS, UMR CNRS","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2617,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.59526559,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"111","last_page":"120"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9950000047683716,"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":0.9950000047683716,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9847000241279602,"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":0.9829999804496765,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7377504706382751},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7234895825386047},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6852329969406128},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.6206211447715759},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5988864302635193},{"id":"https://openalex.org/keywords/3d-reconstruction","display_name":"3D reconstruction","score":0.5418920516967773},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5306174755096436},{"id":"https://openalex.org/keywords/region-growing","display_name":"Region growing","score":0.5288668274879456},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.49013766646385193},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.45251867175102234},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.43691766262054443},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.4203309714794159},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.37684839963912964},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2618717551231384}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7377504706382751},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7234895825386047},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6852329969406128},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.6206211447715759},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5988864302635193},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.5418920516967773},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5306174755096436},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.5288668274879456},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.49013766646385193},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.45251867175102234},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.43691766262054443},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4203309714794159},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.37684839963912964},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2618717551231384},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2461217.2461239","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2461217.2461239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th Spring Conference on Computer Graphics","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-01311443v1","is_oa":false,"landing_page_url":"https://hal.science/hal-01311443","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"SCCG 2011, 27th Spring conference on Computer Graphics, 2011, Vinicn\u00e9, Slovakia. pp. 111-120, &#x27E8;10.1145/2461217.2461239&#x27E9;","raw_type":"Conference papers"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W196194354","https://openalex.org/W1479718318","https://openalex.org/W1508196330","https://openalex.org/W1545349697","https://openalex.org/W1559325012","https://openalex.org/W1565713110","https://openalex.org/W1595254618","https://openalex.org/W1976018540","https://openalex.org/W1997408577","https://openalex.org/W1998387409","https://openalex.org/W2003593922","https://openalex.org/W2008073424","https://openalex.org/W2014447518","https://openalex.org/W2029789722","https://openalex.org/W2036345186","https://openalex.org/W2036403776","https://openalex.org/W2058371413","https://openalex.org/W2071882742","https://openalex.org/W2083008800","https://openalex.org/W2099666252","https://openalex.org/W2100568348","https://openalex.org/W2104246707","https://openalex.org/W2107920575","https://openalex.org/W2108707886","https://openalex.org/W2109324451","https://openalex.org/W2109928907","https://openalex.org/W2115242586","https://openalex.org/W2132269409","https://openalex.org/W2136573752","https://openalex.org/W2145804351","https://openalex.org/W2153419846","https://openalex.org/W2153810084","https://openalex.org/W2154268366","https://openalex.org/W2158595748","https://openalex.org/W2159965356","https://openalex.org/W2162630772","https://openalex.org/W2163598482","https://openalex.org/W2171037500","https://openalex.org/W2171417304","https://openalex.org/W2171493089","https://openalex.org/W2229412420","https://openalex.org/W2611547523","https://openalex.org/W2620513226","https://openalex.org/W2726159304","https://openalex.org/W2784368404","https://openalex.org/W3102998284","https://openalex.org/W4292338746","https://openalex.org/W7073807007"],"related_works":["https://openalex.org/W2368534456","https://openalex.org/W2394279717","https://openalex.org/W2980582925","https://openalex.org/W2364730859","https://openalex.org/W2359699469","https://openalex.org/W2386644571","https://openalex.org/W2619283684","https://openalex.org/W2922069956","https://openalex.org/W2383720950","https://openalex.org/W4281943322"],"abstract_inverted_index":{"Organ":[0],"segmentation":[1,17,33,65,81],"and":[2,34,110,145],"reconstruction":[3,56,139],"are":[4],"useful":[5],"for":[6,54],"many":[7],"clinical":[8],"purpose,":[9],"like":[10],"diagnostic":[11],"aid":[12],"or":[13,47],"therapy":[14],"planification.":[15],"The":[16,92],"literature":[18,42],"is":[19,23,108,111,143],"large.":[20],"However,":[21],"it":[22],"rare":[24],"to":[25,67,134],"find":[26],"a":[27,51,64,122,130],"method":[28,53,142],"which":[29,127],"performs":[30],"both":[31],"organ":[32],"reconstruction.":[35,118],"Moreover,":[36],"the":[37,41,45,69,73,84,87,96,115,138],"major":[38],"part":[39],"of":[40,86],"focuses":[43],"on":[44,126],"liver":[46],"lungs.":[48],"We":[49],"present":[50],"new":[52],"kidney":[55,70,88,103,124],"from":[57,72],"3D":[58,123],"CT":[59],"scan.":[60],"First,":[61],"we":[62,78,120,128],"perform":[63],"stage":[66],"extract":[68],"volume":[71],"greyscale":[74],"image":[75],"stack.":[76],"Then,":[77],"refine":[79],"this":[80],"by":[82],"analyzing":[83],"histogram":[85],"regions":[89],"previously":[90],"segmented.":[91],"refinement":[93],"step":[94],"eliminates":[95],"areas":[97],"that":[98],"was":[99],"incorrectly":[100],"considered":[101],"as":[102],"region.":[104],"A":[105],"point":[106],"cloud":[107],"extracted":[109],"then":[112],"reconstructed":[113],"using":[114],"Poisson":[116],"surface":[117],"Thus,":[119],"obtain":[121],"model":[125],"apply":[129],"post-treatment":[131],"in":[132],"order":[133],"regularize":[135],"it.":[136],"Despite":[137],"step,":[140],"our":[141],"fast":[144],"can":[146],"be":[147],"used":[148],"real-time":[149],"medical":[150],"environment.":[151]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
