{"id":"https://openalex.org/W3162914970","doi":"https://doi.org/10.1109/icpr48806.2021.9411950","title":"Triplet-path Dilated Network for Detection and Segmentation of General Pathological Images","display_name":"Triplet-path Dilated Network for Detection and Segmentation of General Pathological Images","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3162914970","doi":"https://doi.org/10.1109/icpr48806.2021.9411950","mag":"3162914970"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9411950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9411950","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5088401907","display_name":"Jiaqi Luo","orcid":"https://orcid.org/0000-0001-6903-8515"},"institutions":[{"id":"https://openalex.org/I4210108629","display_name":"Computer Network Information Center","ror":"https://ror.org/01s0wyf50","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210108629"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Luo","raw_affiliation_strings":["Beijing Key Laboratory of Network System and Network Culture, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Network System and Network Culture, Beijing, China","institution_ids":["https://openalex.org/I4210108629"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079144156","display_name":"Zhicheng Zhao","orcid":"https://orcid.org/0000-0002-2761-7399"},"institutions":[{"id":"https://openalex.org/I4210108629","display_name":"Computer Network Information Center","ror":"https://ror.org/01s0wyf50","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210108629"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhicheng Zhao","raw_affiliation_strings":["Beijing Key Laboratory of Network System and Network Culture, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Network System and Network Culture, Beijing, China","institution_ids":["https://openalex.org/I4210108629"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101754632","display_name":"Fei Su","orcid":"https://orcid.org/0000-0003-4245-4687"},"institutions":[{"id":"https://openalex.org/I4210108629","display_name":"Computer Network Information Center","ror":"https://ror.org/01s0wyf50","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210108629"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Su","raw_affiliation_strings":["Beijing Key Laboratory of Network System and Network Culture, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Network System and Network Culture, Beijing, China","institution_ids":["https://openalex.org/I4210108629"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015302215","display_name":"Limei Guo","orcid":"https://orcid.org/0000-0003-0430-2914"},"institutions":[{"id":"https://openalex.org/I111483173","display_name":"King University","ror":"https://ror.org/01evb6z23","country_code":"US","type":"education","lineage":["https://openalex.org/I111483173"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Limei Guo","raw_affiliation_strings":["School of Basic Medical Sciences, Third Hospital, Peking University Health Science Center"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Basic Medical Sciences, Third Hospital, Peking University Health Science Center","institution_ids":["https://openalex.org/I111483173","https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.191,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.47655701,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"abs 1906 11118","issue":null,"first_page":"1452","last_page":"1459"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9984999895095825,"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":0.9984999895095825,"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/T10862","display_name":"AI in cancer detection","score":0.9976000189781189,"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"}},{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9909999966621399,"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/computer-science","display_name":"Computer science","score":0.8272795677185059},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7784202694892883},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7542368173599243},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5804962515830994},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5706601142883301},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.541254460811615},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5290863513946533},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5225979089736938},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5119756460189819},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45306122303009033},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4448584318161011},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4443504810333252},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4155840575695038}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8272795677185059},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7784202694892883},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7542368173599243},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5804962515830994},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5706601142883301},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.541254460811615},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5290863513946533},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5225979089736938},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5119756460189819},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45306122303009033},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4448584318161011},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4443504810333252},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4155840575695038},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9411950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9411950","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8775993757","display_name":null,"funder_award_id":"62076033,U193I202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1923697677","https://openalex.org/W1987869189","https://openalex.org/W2144506857","https://openalex.org/W2155813740","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2550409828","https://openalex.org/W2565639579","https://openalex.org/W2567946946","https://openalex.org/W2592905743","https://openalex.org/W2630837129","https://openalex.org/W2768489488","https://openalex.org/W2772723798","https://openalex.org/W2828862258","https://openalex.org/W2884561390","https://openalex.org/W2885343725","https://openalex.org/W2890559758","https://openalex.org/W2891825754","https://openalex.org/W2892300271","https://openalex.org/W2893299523","https://openalex.org/W2914272101","https://openalex.org/W2920326761","https://openalex.org/W2921092847","https://openalex.org/W2934198733","https://openalex.org/W2935891200","https://openalex.org/W2943930495","https://openalex.org/W2946083470","https://openalex.org/W2953559083","https://openalex.org/W2962766617","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W2963840672","https://openalex.org/W2964083058","https://openalex.org/W2981994674","https://openalex.org/W2982331121","https://openalex.org/W2982770724","https://openalex.org/W2988452521","https://openalex.org/W3013530951","https://openalex.org/W3102701618","https://openalex.org/W4288358483","https://openalex.org/W4289489408","https://openalex.org/W6639824700","https://openalex.org/W6696085341","https://openalex.org/W6739696289","https://openalex.org/W6754551840","https://openalex.org/W6765290977"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W4304166257","https://openalex.org/W2949096641","https://openalex.org/W2970686063","https://openalex.org/W4320729701","https://openalex.org/W3034745255","https://openalex.org/W4254103348"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"has":[2],"been":[3],"widely":[4,144],"applied":[5],"in":[6,19,25,81],"the":[7,22,85,135,149,164,169],"field":[8],"of":[9,40,56,87,138,151,168],"medical":[10],"image":[11],"processing.":[12],"However,":[13],"compared":[14],"with":[15,140,158],"flourishing":[16],"visual":[17],"tasks":[18,39],"natural":[20],"images,":[21],"progress":[23],"achieved":[24],"pathological":[26,78,119],"images":[27,142],"is":[28,99,131],"not":[29],"remarkable,":[30],"and":[31,33,59,73,89,104,126,143,155,166],"detection":[32,72,88,154],"segmentation,":[34,90],"which":[35],"are":[36,43,121],"among":[37],"basic":[38],"computer":[41],"vision,":[42],"regarded":[44],"as":[45],"two":[46,173],"independent":[47],"tasks.":[48],"In":[49],"this":[50],"paper,":[51],"we":[52],"make":[53],"full":[54],"use":[55],"existing":[57],"datasets":[58,120,139,174],"construct":[60],"a":[61,91,124],"triplet-path":[62],"network":[63,171],"using":[64],"dilated":[65],"convolutions":[66],"to":[67,83,101,133],"cooperatively":[68],"accomplish":[69],"one-stage":[70],"object":[71,153],"nuclei":[74],"segmentation":[75,157],"for":[76],"general":[77],"images.":[79],"First,":[80],"order":[82],"meet":[84],"requirement":[86],"novel":[92],"structure":[93],"called":[94],"triplet":[95],"feature":[96],"generation":[97],"(TFG)":[98],"designed":[100],"extract":[102],"high-resolution":[103],"multiscale":[105],"features,":[106],"where":[107],"features":[108],"from":[109,176],"different":[110],"layers":[111],"can":[112],"be":[113],"properly":[114],"integrated.":[115],"Second,":[116],"considering":[117],"that":[118],"usually":[122],"small,":[123],"location-aware":[125],"partially":[127],"truncated":[128],"loss":[129],"function":[130],"proposed":[132,170],"improve":[134],"classification":[136],"accuracy":[137],"few":[141],"varying":[145],"targets.":[146],"We":[147],"compare":[148],"performance":[150],"both":[152],"instance":[156],"state-of-the-art":[159],"methods.":[160],"Experimental":[161],"results":[162],"demonstrate":[163],"effectiveness":[165],"efficiency":[167],"on":[172],"collected":[175],"multiple":[177],"organs.":[178]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}