{"id":"https://openalex.org/W4304098615","doi":"https://doi.org/10.1145/3503161.3548192","title":"Finding the Host from the Lesion by Iteratively Mining the Registration Graph","display_name":"Finding the Host from the Lesion by Iteratively Mining the Registration Graph","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4304098615","doi":"https://doi.org/10.1145/3503161.3548192"},"language":"en","primary_location":{"id":"doi:10.1145/3503161.3548192","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3503161.3548192","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3503161.3548192","source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","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":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3503161.3548192","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101323288","display_name":"Zijie Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zijie Yang","raw_affiliation_strings":["The Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences; The University of Chinese Academy of Sciences, Beijing, China","The University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"The Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences; The University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I4210165038"]},{"raw_affiliation_string":"The University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075290241","display_name":"Lingxi Xie","orcid":"https://orcid.org/0000-0003-4831-9451"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingxi Xie","raw_affiliation_strings":["Huawei Technologies Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies Ltd., Beijing, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025959130","display_name":"Xinyue Huo","orcid":"https://orcid.org/0000-0003-1724-9438"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyue Huo","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056776177","display_name":"Sheng Tang","orcid":"https://orcid.org/0000-0003-3573-2407"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheng Tang","raw_affiliation_strings":["The Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences; Research Institute of Intelligent Computing, Zhejiang Lab, Beijing, China","Research Institute of Intelligent Computing, Zhejiang Lab, Beijing, China"],"affiliations":[{"raw_affiliation_string":"The Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences; Research Institute of Intelligent Computing, Zhejiang Lab, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I4210123185","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Research Institute of Intelligent Computing, Zhejiang Lab, Beijing, China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100393506","display_name":"Qi Tian","orcid":"https://orcid.org/0000-0002-7252-5047"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Tian","raw_affiliation_strings":["Huawei Technologies Ltd., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046305086","display_name":"Yongdong Zhang","orcid":"https://orcid.org/0000-0002-1151-1792"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongdong Zhang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101323288"],"corresponding_institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09543745,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"521","issue":null,"first_page":"5913","last_page":"5922"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9988999962806702,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9988999962806702,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9983999729156494,"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/T10862","display_name":"AI in cancer detection","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.6927300691604614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6901450157165527},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.6882525682449341},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.646734356880188},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6441260576248169},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6049824953079224},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5302448272705078},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.48949992656707764},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4379051923751831},{"id":"https://openalex.org/keywords/lesion","display_name":"Lesion","score":0.43145084381103516},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.43119168281555176},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38918647170066833},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36600732803344727},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.17626938223838806},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1473211944103241},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.09811332821846008}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6927300691604614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6901450157165527},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.6882525682449341},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.646734356880188},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6441260576248169},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6049824953079224},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5302448272705078},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.48949992656707764},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4379051923751831},{"id":"https://openalex.org/C2781156865","wikidata":"https://www.wikidata.org/wiki/Q827023","display_name":"Lesion","level":2,"score":0.43145084381103516},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.43119168281555176},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38918647170066833},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36600732803344727},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.17626938223838806},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1473211944103241},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.09811332821846008}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3503161.3548192","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3503161.3548192","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3503161.3548192","source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","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":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3503161.3548192","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3503161.3548192","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3503161.3548192","source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","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":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.5099999904632568,"display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3537652289","display_name":null,"funder_award_id":"61871004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4020255992","display_name":null,"funder_award_id":"Project","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6258415954","display_name":null,"funder_award_id":"Chinese","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G694870490","display_name":null,"funder_award_id":"E141020","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4304098615.pdf","grobid_xml":"https://content.openalex.org/works/W4304098615.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2125637308","https://openalex.org/W2269649163","https://openalex.org/W2412782625","https://openalex.org/W2618237340","https://openalex.org/W2618238923","https://openalex.org/W2705158815","https://openalex.org/W2728648333","https://openalex.org/W2770657900","https://openalex.org/W2791680898","https://openalex.org/W2799738340","https://openalex.org/W2891631795","https://openalex.org/W2912989244","https://openalex.org/W2918257301","https://openalex.org/W2962914239","https://openalex.org/W2964065884","https://openalex.org/W2964227007","https://openalex.org/W2966108228","https://openalex.org/W2978457402","https://openalex.org/W3013056581","https://openalex.org/W3028070348","https://openalex.org/W3087943225","https://openalex.org/W3098181075","https://openalex.org/W3099561884","https://openalex.org/W3104368407","https://openalex.org/W3104625815","https://openalex.org/W3112701542","https://openalex.org/W3138516171","https://openalex.org/W3202876959","https://openalex.org/W4212875960","https://openalex.org/W6601313673"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2358755282","https://openalex.org/W3027020613","https://openalex.org/W2016533837","https://openalex.org/W2625833328","https://openalex.org/W2038239089"],"abstract_inverted_index":{"Voxel-level":[0],"annotation":[1],"has":[2],"always":[3],"been":[4],"a":[5,25,39,71,137],"burden":[6],"of":[7,24,79,121,133,149],"training":[8,52,97],"medical":[9],"image":[10],"segmentation":[11,135],"models.":[12],"This":[13],"paper":[14],"investigates":[15],"an":[16,42],"interesting":[17],"problem":[18],"that":[19],"finds":[20],"the":[21,30,34,51,58,77,83,89,93,96,104,117,131,144],"host":[22],"organ":[23,60,113,151],"lesion":[26,48,81],"without":[27,110],"actually":[28],"labeling":[29],"organ.":[31],"To":[32],"remedy":[33],"missing":[35],"annotation,":[36,114],"we":[37,115],"construct":[38],"graph":[40],"using":[41],"off-the-shelf":[43],"registration":[44,84],"algorithm,":[45],"on":[46,82,103],"which":[47,141],"labels":[49,66,91],"over":[50],"set":[53],"are":[54,67],"accumulated":[55],"to":[56,69,136],"obtain":[57],"pseudo":[59,65,90],"for":[61,123,127],"each":[62,80],"case.":[63],"These":[64],"used":[68],"train":[70],"deep":[72],"network,":[73],"whose":[74],"predictions":[75],"determine":[76],"affinity":[78,94],"graph.":[85],"We":[86],"iteratively":[87],"update":[88],"with":[92,147],"until":[95],"convergence.":[98],"Our":[99],"method":[100],"is":[101],"evaluated":[102],"MSD":[105],"Liver":[106],"and":[107,125,129,152],"KiTS":[108],"datasets,":[109],"seeing":[111],"any":[112],"achieve":[116],"test":[118],"Dice":[119],"score":[120],"93%":[122],"liver":[124],"92%":[126],"kidney,":[128],"boosts":[130],"accuracy":[132],"tumor":[134],"considerable":[138],"degree,":[139],"$3%$,":[140],"even":[142],"surpasses":[143],"model":[145],"trained":[146],"ground-truth":[148],"both":[150],"tumor.":[153]},"counts_by_year":[],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}
