{"id":"https://openalex.org/W4220864982","doi":"https://doi.org/10.1117/12.2611672","title":"Spatial label smoothing via aleatoric uncertainty for bleeding region segmentation from laparoscopic videos","display_name":"Spatial label smoothing via aleatoric uncertainty for bleeding region segmentation from laparoscopic videos","publication_year":2022,"publication_date":"2022-03-31","ids":{"openalex":"https://openalex.org/W4220864982","doi":"https://doi.org/10.1117/12.2611672"},"language":"en","primary_location":{"id":"doi:10.1117/12.2611672","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2611672","pdf_url":null,"source":{"id":"https://openalex.org/S4363607561","display_name":"Medical Imaging 2022: Image Processing","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":"Medical Imaging 2022: Image Processing","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/A5101817199","display_name":"Jie Qiu","orcid":"https://orcid.org/0000-0002-1795-7998"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Jie Qiu","raw_affiliation_strings":["Nagoya Univ. (Japan)"],"affiliations":[{"raw_affiliation_string":"Nagoya Univ. (Japan)","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088647628","display_name":"Yuichiro Hayashi","orcid":null},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuichiro Hayashi","raw_affiliation_strings":["Nagoya Univ. (Japan)"],"affiliations":[{"raw_affiliation_string":"Nagoya Univ. (Japan)","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074920808","display_name":"Masahiro Oda","orcid":"https://orcid.org/0000-0001-7714-422X"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masahiro Oda","raw_affiliation_strings":["Nagoya Univ. (Japan)"],"affiliations":[{"raw_affiliation_string":"Nagoya Univ. (Japan)","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004959911","display_name":"Takayuki Kitasaka","orcid":"https://orcid.org/0000-0003-1648-1999"},"institutions":[{"id":"https://openalex.org/I190508380","display_name":"Aichi Institute of Technology","ror":"https://ror.org/02qsepw74","country_code":"JP","type":"education","lineage":["https://openalex.org/I190508380"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takayuki Kitasaka","raw_affiliation_strings":["Aichi Institute of Technology (Japan)"],"affiliations":[{"raw_affiliation_string":"Aichi Institute of Technology (Japan)","institution_ids":["https://openalex.org/I190508380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007126631","display_name":"Nobuyoshi Takeshita","orcid":"https://orcid.org/0000-0001-8089-7433"},"institutions":[{"id":"https://openalex.org/I4210145079","display_name":"National Cancer Center Hospital East","ror":"https://ror.org/03rm3gk43","country_code":"JP","type":"healthcare","lineage":["https://openalex.org/I4210145079"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nobuyoshi Takeshita","raw_affiliation_strings":["National Cancer Ctr. Hospital East (Japan)"],"affiliations":[{"raw_affiliation_string":"National Cancer Ctr. Hospital East (Japan)","institution_ids":["https://openalex.org/I4210145079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062506663","display_name":"Masaaki Ito","orcid":"https://orcid.org/0000-0002-1101-2707"},"institutions":[{"id":"https://openalex.org/I4210145079","display_name":"National Cancer Center Hospital East","ror":"https://ror.org/03rm3gk43","country_code":"JP","type":"healthcare","lineage":["https://openalex.org/I4210145079"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaaki Ito","raw_affiliation_strings":["National Cancer Ctr. Hospital East (Japan)"],"affiliations":[{"raw_affiliation_string":"National Cancer Ctr. Hospital East (Japan)","institution_ids":["https://openalex.org/I4210145079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032527419","display_name":"Kensaku Mori","orcid":"https://orcid.org/0000-0002-0100-4797"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]},{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kensaku Mori","raw_affiliation_strings":["Nagoya Univ. (Japan)","National Institute of Informatics (Japan)"],"affiliations":[{"raw_affiliation_string":"Nagoya Univ. (Japan)","institution_ids":["https://openalex.org/I60134161"]},{"raw_affiliation_string":"National Institute of Informatics (Japan)","institution_ids":["https://openalex.org/I184597095"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101817199"],"corresponding_institution_ids":["https://openalex.org/I60134161"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01354627,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":null,"first_page":"32","last_page":"32"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9993000030517578,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9993000030517578,"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/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.9860000014305115,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.8381031155586243},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7734602689743042},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7719618678092957},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6165399551391602},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.574441134929657},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5273588299751282},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5127766728401184},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5073453783988953},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.44724833965301514},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4372003972530365},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42685651779174805},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.359445184469223},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3368775248527527}],"concepts":[{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.8381031155586243},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7734602689743042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7719618678092957},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6165399551391602},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.574441134929657},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5273588299751282},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5127766728401184},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5073453783988953},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.44724833965301514},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4372003972530365},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42685651779174805},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.359445184469223},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3368775248527527}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2611672","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2611672","pdf_url":null,"source":{"id":"https://openalex.org/S4363607561","display_name":"Medical Imaging 2022: Image Processing","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":"Medical Imaging 2022: Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","score":0.4000000059604645,"display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2095705004","https://openalex.org/W2560311620","https://openalex.org/W2600383743","https://openalex.org/W2887976372","https://openalex.org/W2948210185","https://openalex.org/W3173685130","https://openalex.org/W3176597251","https://openalex.org/W4238549709","https://openalex.org/W6617145748","https://openalex.org/W6639824700","https://openalex.org/W6674330103","https://openalex.org/W6686164453","https://openalex.org/W6687483927","https://openalex.org/W6735443497","https://openalex.org/W6738279954","https://openalex.org/W6749493692","https://openalex.org/W6774433549"],"related_works":["https://openalex.org/W1978572805","https://openalex.org/W2383807498","https://openalex.org/W1997992934","https://openalex.org/W1987225439","https://openalex.org/W4238188170","https://openalex.org/W2125114371","https://openalex.org/W2019977573","https://openalex.org/W2149980199","https://openalex.org/W3125766170","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Automatically":[0],"segmenting":[1],"bleeding":[2,133],"regions":[3],"is":[4,42,90],"an":[5,39,66,93],"essential":[6],"task":[7],"for":[8,83,143],"computer-assisted":[9],"surgery":[10],"systems.":[11],"Recent":[12],"development":[13],"in":[14,30,36,114,130],"deep":[15,27,97],"learning":[16],"has":[17],"boosted":[18],"the":[19,56,59,101,110,120,127,139],"performance":[20],"of":[21,72,96,103,122],"medical":[22],"image":[23],"segmentation.":[24],"However,":[25],"training":[26],"neural":[28,98],"networks,":[29],"general,":[31],"requires":[32],"high-quality":[33],"pixel-wise":[34],"annotations,":[35],"which":[37,81],"such":[38,86],"annotating":[40],"process":[41],"expensive":[43],"and":[44],"easy":[45],"to":[46],"introduce":[47],"annotation":[48,88],"noise.":[49],"To":[50],"address":[51],"this":[52],"issue,":[53],"motivated":[54],"by":[55,125],"observation":[57],"that":[58],"noise":[60,85],"should":[61],"be":[62],"data-dependent,":[63],"we":[64,107],"propose":[65],"uncertainty-guided":[67],"label":[68,76,112],"smoothing":[69,77,113],"method":[70],"instead":[71],"using":[73],"a":[74,115,131],"fixed":[75],"strategy.":[78],"Aleatoric":[79],"uncertainty,":[80,106],"accounts":[82],"inherent":[84],"as":[87],"error,":[89],"estimated":[91,104],"via":[92],"additional":[94],"branch":[95],"networks.":[99],"With":[100],"help":[102],"aleatoric":[105],"could":[108],"guide":[109],"spatial":[111],"self-adaptive":[116],"manner.":[117],"We":[118],"demonstrated":[119],"effectiveness":[121],"our":[123,144],"proposal":[124],"evaluating":[126],"Dice":[128],"coefficient":[129],"private":[132],"segmentation":[134],"dataset.":[135],"An":[136],"improvement":[137],"over":[138],"baseline":[140],"was":[141],"observed":[142],"proposal.":[145]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}