{"id":"https://openalex.org/W4312905185","doi":"https://doi.org/10.1109/icpr56361.2022.9956530","title":"Pixel-accurate Segmentation of Surgical Tools based on Bounding Box Annotations","display_name":"Pixel-accurate Segmentation of Surgical Tools based on Bounding Box Annotations","publication_year":2022,"publication_date":"2022-08-21","ids":{"openalex":"https://openalex.org/W4312905185","doi":"https://doi.org/10.1109/icpr56361.2022.9956530"},"language":"en","primary_location":{"id":"doi:10.1109/icpr56361.2022.9956530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956530","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 26th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"article","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/A5020974986","display_name":"George Leifman","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"George Leifman","raw_affiliation_strings":["Google Research"],"affiliations":[{"raw_affiliation_string":"Google Research","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030532654","display_name":"Amit Aides","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amit Aides","raw_affiliation_strings":["Google Research"],"affiliations":[{"raw_affiliation_string":"Google Research","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022512211","display_name":"Tomer Golany","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tomer Golany","raw_affiliation_strings":["Google Research"],"affiliations":[{"raw_affiliation_string":"Google Research","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070161627","display_name":"Daniel Z. Freedman","orcid":"https://orcid.org/0000-0001-7354-0129"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Freedman","raw_affiliation_strings":["Google Research"],"affiliations":[{"raw_affiliation_string":"Google Research","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024009299","display_name":"Ehud Rivlin","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ehud Rivlin","raw_affiliation_strings":["Google Research"],"affiliations":[{"raw_affiliation_string":"Google Research","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5020974986"],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":1.9225,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.87748944,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5096","last_page":"5103"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9947999715805054,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9947999715805054,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9908000230789185,"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/T11984","display_name":"Anatomy and Medical Technology","score":0.989799976348877,"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/minimum-bounding-box","display_name":"Minimum bounding box","score":0.8081361055374146},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7158621549606323},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6566888093948364},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6556599140167236},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.5908467769622803},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5398565530776978},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5201542973518372},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49974918365478516},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23972773551940918}],"concepts":[{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.8081361055374146},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7158621549606323},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6566888093948364},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6556599140167236},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5908467769622803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5398565530776978},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5201542973518372},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49974918365478516},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23972773551940918}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr56361.2022.9956530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956530","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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":54,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1884191083","https://openalex.org/W2098074239","https://openalex.org/W2100836452","https://openalex.org/W2124351162","https://openalex.org/W2179331991","https://openalex.org/W2266464013","https://openalex.org/W2307770531","https://openalex.org/W2412782625","https://openalex.org/W2657144928","https://openalex.org/W2772901904","https://openalex.org/W2782757030","https://openalex.org/W2792767783","https://openalex.org/W2802208855","https://openalex.org/W2804047627","https://openalex.org/W2915738519","https://openalex.org/W2948778231","https://openalex.org/W2962793481","https://openalex.org/W2963150697","https://openalex.org/W2963647178","https://openalex.org/W2963794428","https://openalex.org/W2963881378","https://openalex.org/W2964309882","https://openalex.org/W2979328438","https://openalex.org/W2979609563","https://openalex.org/W2979922443","https://openalex.org/W2995784156","https://openalex.org/W3004790497","https://openalex.org/W3011409570","https://openalex.org/W3096104140","https://openalex.org/W3096667748","https://openalex.org/W3096724473","https://openalex.org/W3098152091","https://openalex.org/W3108141367","https://openalex.org/W3126035648","https://openalex.org/W3127268207","https://openalex.org/W3128248230","https://openalex.org/W3129553451","https://openalex.org/W3145199835","https://openalex.org/W3160993888","https://openalex.org/W3208026280","https://openalex.org/W4288574670","https://openalex.org/W4289489408","https://openalex.org/W6639102338","https://openalex.org/W6674558680","https://openalex.org/W6697925102","https://openalex.org/W6747680804","https://openalex.org/W6748481559","https://openalex.org/W6751430876","https://openalex.org/W6754551840","https://openalex.org/W6758742486","https://openalex.org/W6760424586","https://openalex.org/W6761578041","https://openalex.org/W6771788566"],"related_works":["https://openalex.org/W4237171675","https://openalex.org/W3036286480","https://openalex.org/W4287027631","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W4390524233"],"abstract_inverted_index":{"Detection":[0],"and":[1,41,90,112],"segmentation":[2,16,59],"of":[3,25,77,84,105],"surgical":[4,33],"instruments":[5],"is":[6,17,68,88],"an":[7,66],"important":[8],"problem":[9,60],"for":[10,22,147],"laparoscopic":[11],"surgery.":[12],"Accurate":[13],"pixel-wise":[14],"instrument":[15,53,71,149],"a":[18,48,117,130],"useful":[19],"intermediate":[20],"task":[21],"the":[23,57,82,106,125],"development":[24],"computer-assisted":[26],"surgery":[27],"systems,":[28],"such":[29],"as":[30,70,102],"pose":[31],"estimation,":[32,35],"phase":[34],"enhanced":[36],"image":[37,67],"fusion,":[38],"video":[39],"retrieval":[40],"others.":[42],"In":[43],"this":[44],"paper":[45],"we":[46,128],"describe":[47],"deep":[49],"learning-based":[50],"approach":[51,79,96,132,139],"to":[52,81,92,114,122,133],"segmentation,":[54,150],"which":[55,62,87,108],"addresses":[56],"binary":[58],"in":[61,65],"every":[63],"pixel":[64],"labeled":[69],"or":[72],"background.":[73],"The":[74],"key":[75],"novelty":[76],"our":[78,95],"relates":[80],"use":[83],"training":[85,136],"data":[86],"inexpensive":[89],"fast":[91],"acquire.":[93],"First,":[94],"relies":[97],"on":[98,153],"weak":[99,154],"annotations":[100],"provided":[101],"bounding":[103],"boxes":[104],"instruments,":[107],"are":[109],"much":[110],"faster":[111],"cheaper":[113],"obtain":[115],"than":[116],"dense":[118],"pixel-level":[119],"annotations.":[120,155],"Second,":[121],"further":[123],"improve":[124],"system\u2019s":[126],"accuracy":[127],"propose":[129],"novel":[131],"generate":[134],"synthetic":[135],"images.":[137],"Our":[138],"achieves":[140],"state-of-the-art":[141],"results,":[142],"outperforming":[143],"previously":[144],"proposed":[145],"methods":[146],"automatic":[148],"based":[151],"only":[152]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2026-02-28T09:26:25.869077","created_date":"2025-10-10T00:00:00"}