{"id":"https://openalex.org/W3011870432","doi":"https://doi.org/10.1117/12.2550511","title":"Fine-grained tumor segmentation on computed tomography slices by leveraging bottom-up and top-down strategies","display_name":"Fine-grained tumor segmentation on computed tomography slices by leveraging bottom-up and top-down strategies","publication_year":2020,"publication_date":"2020-03-10","ids":{"openalex":"https://openalex.org/W3011870432","doi":"https://doi.org/10.1117/12.2550511","mag":"3011870432"},"language":"en","primary_location":{"id":"doi:10.1117/12.2550511","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2550511","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Image Processing","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/A5070531457","display_name":"Zhenmei Yu","orcid":"https://orcid.org/0000-0003-1899-0850"},"institutions":[{"id":"https://openalex.org/I4210151294","display_name":"Shandong Women\u2019s University","ror":"https://ror.org/03rp8h078","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151294"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenmei Yu","raw_affiliation_strings":["Shandong Women's Univ. (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Women's Univ. (China)","institution_ids":["https://openalex.org/I4210151294"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088461583","display_name":"Shuchao Pang","orcid":"https://orcid.org/0000-0002-5668-833X"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shuchao Pang","raw_affiliation_strings":["Macquarie Univ. (Australia)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Macquarie Univ. (Australia)","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108270107","display_name":"Anan Du","orcid":null},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Anan Du","raw_affiliation_strings":["Univ. of Technology Sydney (Australia)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Technology Sydney (Australia)","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010152619","display_name":"Mehmet A. Orgun","orcid":"https://orcid.org/0000-0002-7873-1562"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mehmet A. Orgun","raw_affiliation_strings":["Macquarie Univ. (Australia)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Macquarie Univ. (Australia)","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100322712","display_name":"Yan Wang","orcid":"https://orcid.org/0000-0002-5344-1884"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yan Wang","raw_affiliation_strings":["Macquarie Univ. (Australia)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Macquarie Univ. (Australia)","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058323321","display_name":"Hong Lin","orcid":"https://orcid.org/0000-0003-1827-5507"},"institutions":[{"id":"https://openalex.org/I16277215","display_name":"University of Houston - Downtown","ror":"https://ror.org/05mj6fy81","country_code":"US","type":"education","lineage":["https://openalex.org/I16277215"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hong Lin","raw_affiliation_strings":["Univ. of Houston-Downtown (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Houston-Downtown (United States)","institution_ids":["https://openalex.org/I16277215"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9987999796867371,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9930999875068665,"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":0.803638219833374},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.787324070930481},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6791435480117798},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6418834924697876},{"id":"https://openalex.org/keywords/top-down-and-bottom-up-design","display_name":"Top-down and bottom-up design","score":0.5970185995101929},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5379564762115479},{"id":"https://openalex.org/keywords/jaccard-index","display_name":"Jaccard index","score":0.5248863101005554},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.520523190498352},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4986743927001953},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.48593464493751526},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48119646310806274},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47303149104118347},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4573156535625458},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.45196446776390076},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4384562075138092},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.4311394989490509},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2515530586242676}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.803638219833374},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.787324070930481},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6791435480117798},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6418834924697876},{"id":"https://openalex.org/C135798126","wikidata":"https://www.wikidata.org/wiki/Q2167279","display_name":"Top-down and bottom-up design","level":2,"score":0.5970185995101929},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5379564762115479},{"id":"https://openalex.org/C203519979","wikidata":"https://www.wikidata.org/wiki/Q865360","display_name":"Jaccard index","level":3,"score":0.5248863101005554},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.520523190498352},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4986743927001953},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.48593464493751526},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48119646310806274},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47303149104118347},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4573156535625458},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.45196446776390076},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4384562075138092},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.4311394989490509},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2515530586242676},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2550511","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2550511","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Image Processing","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":0,"referenced_works":[],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2945274617","https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W4368283028","https://openalex.org/W2055202857","https://openalex.org/W2371519352","https://openalex.org/W4205800335","https://openalex.org/W2386644571","https://openalex.org/W2372421320"],"abstract_inverted_index":{"Fully":[0],"Convolutional":[1],"Neural":[2],"Networks":[3],"(FCNNs)":[4],"have":[5],"been":[6],"widely":[7],"employed":[8],"to":[9,86,153],"solve":[10,87],"object":[11,29,98,216],"segmentation":[12,120,145,203,217],"tasks":[13],"effectively":[14],"in":[15,25,37,64],"both":[16],"the":[17,45,51,118,137,142,161,167,172,190,226],"computer":[18],"vision":[19],"and":[20,100,182,192,205],"medical":[21],"image":[22,75],"processing":[23],"fields":[24],"recent":[26],"years.":[27],"In":[28,84],"segmentation,":[30],"FCNNs":[31,68],"play":[32],"a":[33,92,113,123,150],"pixel-level":[34],"prediction":[35],"role":[36],"generating":[38],"segmented":[39],"predictions":[40],"pixel-by-pixel,":[41],"but":[42,77],"they":[43,78],"ignore":[44],"relationships":[46],"among":[47,239],"generated":[48],"pixels":[49],"on":[50,105,222],"output":[52],"image.":[53],"Moreover,":[54,103],"blurry":[55],"boundaries":[56],"of":[57,73,136,144,164,174,229],"predicted":[58],"objects":[59],"are":[60],"another":[61],"common":[62,223],"obstacle":[63],"this":[65],"task,":[66],"because":[67],"usually":[69,134],"generate":[70],"low-frequency":[71],"components":[72],"an":[74],"well,":[76],"lack":[79],"clear":[80],"high-frequency":[81],"information":[82],"inside.":[83],"order":[85],"these":[88],"problems,":[89],"we":[90,111,116],"introduce":[91],"top-down":[93,193],"strategy":[94],"by":[95,126],"globally":[96,159],"considering":[97],"shapes":[99],"context":[101],"information.":[102],"based":[104],"original":[106],"pixel-wise":[107],"loss":[108,152,169],"functions":[109],"which":[110,132],"call":[112],"bottom-up":[114,191],"strategy,":[115],"formulate":[117],"tumor":[119,180,202],"task":[121],"as":[122],"regression":[124],"problem":[125],"using":[127],"Jaccard":[128],"Similarity":[129],"Coefficient":[130],"(JSC)":[131],"is":[133],"one":[135],"main":[138],"metrics":[139,224],"for":[140,158,214,233],"evaluating":[141,160],"performance":[143,228],"methods.":[146],"We":[147],"directly":[148],"propose":[149],"JSC":[151],"further":[154],"optimize":[155],"network":[156],"parameters":[157],"whole":[162],"outputs":[163],"tumors.":[165],"Furthermore,":[166],"new":[168],"also":[170,206],"alleviates":[171],"effect":[173],"severe":[175],"class":[176],"imbalanced":[177],"problems":[178],"between":[179],"regions":[181,184],"non-tumor":[183],"when":[185],"training":[186],"FCNNs.":[187],"By":[188],"leveraging":[189],"strategies":[194],"together,":[195],"our":[196,230],"model":[197],"can":[198],"obtain":[199],"more":[200,240],"fine-grained":[201],"results":[204,221],"be":[207],"easily":[208],"embedded":[209],"into":[210],"any":[211],"FCNN":[212],"framework":[213],"other":[215],"tasks.":[218],"Detailed":[219],"experimental":[220],"demonstrate":[225],"superior":[227],"proposed":[231],"method":[232],"Kidney":[234],"Tumor":[235],"Segmentation":[236],"Challenge":[237],"2019":[238],"than":[241],"100":[242],"involved":[243],"teams.":[244]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
