{"id":"https://openalex.org/W4416961737","doi":"https://doi.org/10.1109/ist66504.2025.11268430","title":"Statistical shape model for anatomical landmarks prediction in humerus and mixed reality visualization","display_name":"Statistical shape model for anatomical landmarks prediction in humerus and mixed reality visualization","publication_year":2025,"publication_date":"2025-10-15","ids":{"openalex":"https://openalex.org/W4416961737","doi":"https://doi.org/10.1109/ist66504.2025.11268430"},"language":"en","primary_location":{"id":"doi:10.1109/ist66504.2025.11268430","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ist66504.2025.11268430","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Imaging Systems and Techniques (IST)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.1109/IST66504.2025.11268430","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120540815","display_name":"Gianni Magrini","orcid":null},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Gianni Magrini","raw_affiliation_strings":["Politecnico di Milano MedApp S.A"],"affiliations":[{"raw_affiliation_string":"Politecnico di Milano MedApp S.A","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081725595","display_name":"Maciej Stanuch","orcid":"https://orcid.org/0000-0002-6764-3815"},"institutions":[{"id":"https://openalex.org/I1283576576","display_name":"NetApp (United States)","ror":"https://ror.org/05c4cm338","country_code":"US","type":"company","lineage":["https://openalex.org/I1283576576"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maciej Stanuch","raw_affiliation_strings":["MedApp S.A"],"affiliations":[{"raw_affiliation_string":"MedApp S.A","institution_ids":["https://openalex.org/I1283576576"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073000204","display_name":"Andrzej Skalski","orcid":"https://orcid.org/0000-0003-2299-458X"},"institutions":[{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Andrzej Skalski","raw_affiliation_strings":["AGH University of Krakow MedApp S.A"],"affiliations":[{"raw_affiliation_string":"AGH University of Krakow MedApp S.A","institution_ids":["https://openalex.org/I686019"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5120540815"],"corresponding_institution_ids":["https://openalex.org/I93860229"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.39748876,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11984","display_name":"Anatomy and Medical Technology","score":0.5238000154495239,"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"}},"topics":[{"id":"https://openalex.org/T11984","display_name":"Anatomy and Medical Technology","score":0.5238000154495239,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.1835000067949295,"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/T10916","display_name":"Surgical Simulation and Training","score":0.04479999840259552,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/visualization","display_name":"Visualization","score":0.6348000168800354},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.532800018787384},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5285999774932861},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.48750001192092896},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4156000018119812},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4032000005245209},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.3910999894142151},{"id":"https://openalex.org/keywords/active-shape-model","display_name":"Active shape model","score":0.3853999972343445}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6797999739646912},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6348000168800354},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5666999816894531},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.532800018787384},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5297999978065491},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5285999774932861},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.48750001192092896},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4156000018119812},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4032000005245209},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3910999894142151},{"id":"https://openalex.org/C129641003","wikidata":"https://www.wikidata.org/wiki/Q267189","display_name":"Active shape model","level":3,"score":0.3853999972343445},{"id":"https://openalex.org/C3019007443","wikidata":"https://www.wikidata.org/wiki/Q568742","display_name":"3d model","level":2,"score":0.3840999901294708},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.3488999903202057},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3328000009059906},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.3260999917984009},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3075999915599823},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.30169999599456787},{"id":"https://openalex.org/C3019060180","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automated method","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.275299996137619},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C2777897806","wikidata":"https://www.wikidata.org/wiki/Q568742","display_name":"3D modeling","level":2,"score":0.2572000026702881}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ist66504.2025.11268430","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ist66504.2025.11268430","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Imaging Systems and Techniques (IST)","raw_type":"proceedings-article"},{"id":"pmh:oai:zenodo.org:17397347","is_oa":true,"landing_page_url":"https://doi.org/10.1109/IST66504.2025.11268430","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IST, 2025 IEEE International Conference on Imaging Systems and Techniques, Strasbourg, France, 15-17 October 2025","raw_type":"info:eu-repo/semantics/conferencePaper"}],"best_oa_location":{"id":"pmh:oai:zenodo.org:17397347","is_oa":true,"landing_page_url":"https://doi.org/10.1109/IST66504.2025.11268430","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IST, 2025 IEEE International Conference on Imaging Systems and Techniques, Strasbourg, France, 15-17 October 2025","raw_type":"info:eu-repo/semantics/conferencePaper"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1995003188","https://openalex.org/W2026616100","https://openalex.org/W2038952578","https://openalex.org/W2049981393","https://openalex.org/W2104276184","https://openalex.org/W2119851068","https://openalex.org/W2168722300","https://openalex.org/W2170473296","https://openalex.org/W2248684199","https://openalex.org/W2899641089","https://openalex.org/W3025709688","https://openalex.org/W3127523954","https://openalex.org/W3164425762","https://openalex.org/W3215105773","https://openalex.org/W4303700202","https://openalex.org/W4304633197","https://openalex.org/W4321769412","https://openalex.org/W4383218413","https://openalex.org/W4390791008","https://openalex.org/W4410235049"],"related_works":[],"abstract_inverted_index":{"This":[0,79,182],"work":[1],"presents":[2],"an":[3],"automated":[4,76,90],"pipeline":[5,108],"for":[6,120,141,154],"statistical":[7],"shape":[8],"modeling":[9],"and":[10,19,32,40,57,63,125,128,150],"evaluation":[11],"of":[12,30,83,130,143,157,179,195],"3D":[13,112],"anatomical":[14,41],"landmarks":[15,67,86,118],"in":[16,59,72,87,102,187],"the":[17,85,93,97,131,144,168,193,199],"left":[18,62,149],"right":[20,64,152],"humeri":[21],"from":[22,111,172],"Computed":[23],"Tomography":[24],"(CT)":[25],"data.":[26],"The":[27,43,107],"process":[28],"consists":[29],"training":[31,121],"testing":[33],"stages,":[34],"designed":[35,46],"to":[36,47,51,95,166],"ensure":[37],"reproducibility,":[38],"robustness,":[39],"accuracy.":[42],"model":[44,80,132,183,200],"is":[45,81,164,201],"reduce":[48],"bias":[49],"related":[50],"template":[52,139],"selection,":[53],"human":[54,190],"selection":[55,119,140],"variability,":[56],"differences":[58],"laterality":[60],"between":[61],"humeri.":[65],"Anatomical":[66],"play":[68],"a":[69,88,103,155,176],"pivotal":[70],"role":[71],"semi-":[73],"or":[74],"fully":[75,89],"implant":[77],"placement.":[78],"capable":[82],"predicting":[84],"way":[91],"with":[92,137,189],"possibility":[94],"adjust":[96],"results":[98,186],"manually,":[99],"if":[100],"needed,":[101],"mixed":[104],"reality":[105],"environment.":[106],"involves":[109],"segmentation":[110],"medical":[113],"images":[114],"(CT":[115],"scans),":[116],"manual":[117],"images,":[122],"meshing,":[123],"rigid":[124],"non-rigid":[126],"registration,":[127],"cross-validation":[129],"by":[133],"performing":[134],"10":[135,151],"predictions":[136],"different":[138],"each":[142],"20":[145],"test":[146],"cases":[147],"(10":[148],"humeri)":[153],"total":[156,177],"200":[158],"predictions.":[159],"An":[160],"interobserver":[161],"variability":[162],"study":[163],"conducted":[165],"validate":[167],"model,":[169],"utilizing":[170],"annotations":[171],"5":[173],"operators":[174],"(for":[175],"number":[178],"50":[180],"annotations).":[181],"shows":[184],"comparable":[185],"comparison":[188],"annotation,":[191],"having":[192],"advantage":[194],"being":[196],"automatic":[197],"once":[198],"trained.":[202]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-12-03T00:00:00"}