{"id":"https://openalex.org/W2971056113","doi":"https://doi.org/10.1109/icip.2019.8803730","title":"Multi-Stream Scale-Insensitive Convolutional and Recurrent Neural Networks for Liver Tumor Detection in Dynamic Ct Images","display_name":"Multi-Stream Scale-Insensitive Convolutional and Recurrent Neural Networks for Liver Tumor Detection in Dynamic Ct Images","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2971056113","doi":"https://doi.org/10.1109/icip.2019.8803730","mag":"2971056113"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8803730","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803730","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","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/A5025474414","display_name":"Dong Liang","orcid":"https://orcid.org/0000-0001-6257-0875"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Liang","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057181928","display_name":"Ruofeng Tong","orcid":"https://orcid.org/0000-0002-8167-5354"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruofeng Tong","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071068569","display_name":"Jian Wu","orcid":"https://orcid.org/0000-0002-3230-6392"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wu","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090814258","display_name":"Lanfen Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lanfen Lin","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101998864","display_name":"Xiao Chen","orcid":"https://orcid.org/0000-0002-1332-0535"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Chen","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057452864","display_name":"Hongjie Hu","orcid":"https://orcid.org/0000-0002-9859-5860"},"institutions":[{"id":"https://openalex.org/I2802390878","display_name":"Sir Run Run Shaw Hospital","ror":"https://ror.org/00ka6rp58","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2802390878"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongjie Hu","raw_affiliation_strings":["Sir Run Run Shaw Hospital, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sir Run Run Shaw Hospital, Hangzhou, China","institution_ids":["https://openalex.org/I2802390878"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089515172","display_name":"Qiaowei Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiaowei Zhang","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100738365","display_name":"Qingqing Chen","orcid":"https://orcid.org/0000-0003-2268-1938"},"institutions":[{"id":"https://openalex.org/I2802390878","display_name":"Sir Run Run Shaw Hospital","ror":"https://ror.org/00ka6rp58","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2802390878"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingqing Chen","raw_affiliation_strings":["Sir Run Run Shaw Hospital, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sir Run Run Shaw Hospital, Hangzhou, China","institution_ids":["https://openalex.org/I2802390878"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010434486","display_name":"Yutaro Iwamoto","orcid":"https://orcid.org/0000-0001-6723-8652"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yutaro Iwamoto","raw_affiliation_strings":["Ritsumeikan University, Kusatsu, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ritsumeikan University, Kusatsu, Japan","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086851360","display_name":"Xian\u2010Hua Han","orcid":"https://orcid.org/0000-0002-5003-3180"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xianhua Han","raw_affiliation_strings":["Ritsumeikan University, Kusatsu, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ritsumeikan University, Kusatsu, Japan","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044216245","display_name":"Yen\u2010Wei Chen","orcid":"https://orcid.org/0000-0002-5952-0188"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yen-Wei Chen","raw_affiliation_strings":["Ritsumeikan University, Kusatsu, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ritsumeikan University, Kusatsu, Japan","institution_ids":["https://openalex.org/I135768898"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"794","last_page":"798"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T11019","display_name":"Image Enhancement Techniques","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/T10862","display_name":"AI in cancer detection","score":0.9973000288009644,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8177851438522339},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7693194150924683},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6411121487617493},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.525230884552002},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5188180804252625},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5049481987953186},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4197835922241211},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3830024302005768}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8177851438522339},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7693194150924683},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6411121487617493},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.525230884552002},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5188180804252625},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5049481987953186},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4197835922241211},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3830024302005768},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2019.8803730","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803730","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1903029394","https://openalex.org/W2144554289","https://openalex.org/W2890136754","https://openalex.org/W2962810613","https://openalex.org/W2962850830","https://openalex.org/W2963338899"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2969228573","https://openalex.org/W2963690996","https://openalex.org/W3127668761"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1,97],"networks":[2],"(CNNs)":[3],"have":[4,14,152],"achieved":[5],"great":[6,15],"success":[7],"in":[8,20,39,158],"numerous":[9],"challenging":[10],"vision":[11],"tasks,":[12],"and":[13,66,95],"potential":[16],"for":[17,50,71,100,145],"object":[18],"detection":[19,77,146],"natural":[21,26],"images.":[22,59],"Compared":[23],"with":[24,78],"the":[25,56,107,130,154],"images,":[27],"medical":[28],"images":[29],"exhibit":[30],"some":[31],"unique":[32],"characteristics.":[33],"Therefore,":[34],"substantial":[35],"challenges":[36],"still":[37],"remain":[38],"this":[40,87],"field.":[41],"The":[42],"first":[43],"challenge":[44],"is":[45,83,121],"to":[46,116],"develop":[47],"a":[48,79,91,124],"method":[49],"effectively":[51],"distilling":[52],"enhancement":[53,118],"patterns":[54],"from":[55],"dynamic":[57],"CT":[58],"Moreover,":[60],"since":[61],"tumor":[62,74,102],"sizes":[63],"vary":[64],"greatly":[65],"small":[67],"lesions":[68],"are":[69],"important":[70],"early":[72],"liver":[73,101,149],"detection,":[75],"lesion":[76],"widely":[80],"variable":[81],"scale":[82],"another":[84],"challenge.":[85],"In":[86],"paper,":[88],"we":[89,105],"propose":[90,106],"multi-stream":[92],"scale-insensitive":[93],"convolutional":[94,111],"recurrent":[96],"network":[98],"(MSCR)":[99],"detection.":[103],"Specifically,":[104],"use":[108],"of":[109,143,147,156],"grouped":[110],"long":[112],"short-term":[113],"memory":[114],"(GCLSTM)":[115],"extract":[117],"patterns,":[119],"which":[120],"developed":[122],"as":[123],"plug-and-play":[125],"module.":[126],"Experiments":[127],"show":[128],"that":[129],"MSCR":[131,157],"framework":[132],"exhibits":[133],"superior":[134],"performance":[135],"over":[136],"state-of-the-art":[137],"approaches,":[138],"achieving":[139],"an":[140],"average":[141],"precision":[142],"77.06%":[144],"focal":[148],"lesions.":[150],"We":[151],"released":[153],"code":[155],"<sup":[159],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[160],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>":[161],".":[162]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
