{"id":"https://openalex.org/W3159272159","doi":"https://doi.org/10.1109/tmi.2021.3077285","title":"Object-Guided Instance Segmentation With Auxiliary Feature Refinement for Biological Images","display_name":"Object-Guided Instance Segmentation With Auxiliary Feature Refinement for Biological Images","publication_year":2021,"publication_date":"2021-05-04","ids":{"openalex":"https://openalex.org/W3159272159","doi":"https://doi.org/10.1109/tmi.2021.3077285","mag":"3159272159","pmid":"https://pubmed.ncbi.nlm.nih.gov/33945472"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2021.3077285","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2021.3077285","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2106.07159","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jingru Yi","orcid":"https://orcid.org/0000-0001-9648-9389"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jingru Yi","raw_affiliation_strings":["Rutgers University, Piscataway, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Rutgers University, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Pengxiang Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pengxiang Wu","raw_affiliation_strings":["Rutgers University, Piscataway, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Rutgers University, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hui Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hui Tang","raw_affiliation_strings":["Tencent Hippocrates Research Labs, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Tencent Hippocrates Research Labs, Palo Alto, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bo Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Liu","raw_affiliation_strings":["Rutgers University, Piscataway, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Rutgers University, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qiaoying Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiaoying Huang","raw_affiliation_strings":["Rutgers University, Piscataway, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Rutgers University, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hui Qu","orcid":"https://orcid.org/0000-0002-4260-3809"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hui Qu","raw_affiliation_strings":["Rutgers University, Piscataway, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Rutgers University, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lianyi Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lianyi Han","raw_affiliation_strings":["Tencent Hippocrates Research Labs, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Tencent Hippocrates Research Labs, Palo Alto, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Fan","raw_affiliation_strings":["Tencent Hippocrates Research Labs, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Tencent Hippocrates Research Labs, Palo Alto, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Daniel J. Hoeppner","orcid":null},"institutions":[{"id":"https://openalex.org/I4210151493","display_name":"Lieber Institute for Brain Development","ror":"https://ror.org/04q36wn27","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210151493"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel J. Hoeppner","raw_affiliation_strings":["Lieber Institute for Brain Development, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Lieber Institute for Brain Development, Baltimore, MD, USA","institution_ids":["https://openalex.org/I4210151493"]}]},{"author_position":"last","author":{"id":null,"display_name":"Dimitris N. Metaxas","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dimitris N. Metaxas","raw_affiliation_strings":["Rutgers University, Piscataway, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Rutgers University, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":10,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I102322142"],"apc_list":null,"apc_paid":null,"fwci":1.5536,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.84874778,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"40","issue":"9","first_page":"2403","last_page":"2414"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.37700000405311584,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.37700000405311584,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.29100000858306885,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.17569999396800995,"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/minimum-bounding-box","display_name":"Minimum bounding box","score":0.8266000151634216},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.8137999773025513},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.7053999900817871},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6517999768257141},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.6266000270843506},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.5949000120162964},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.578499972820282},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5583999752998352}],"concepts":[{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.8266000151634216},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8137999773025513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7623999714851379},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7196000218391418},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.7053999900817871},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6517999768257141},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.6266000270843506},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5949000120162964},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.578499972820282},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5724999904632568},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5583999752998352},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.42410001158714294},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4174000024795532},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4041000008583069},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.39320001006126404},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.3734999895095825},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3109999895095825},{"id":"https://openalex.org/C42314347","wikidata":"https://www.wikidata.org/wiki/Q6865488","display_name":"Minimum spanning tree-based segmentation","level":5,"score":0.31049999594688416},{"id":"https://openalex.org/C67561299","wikidata":"https://www.wikidata.org/wiki/Q7292710","display_name":"Range segmentation","level":5,"score":0.2992999851703644},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.2648000121116638}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tmi.2021.3077285","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2021.3077285","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:33945472","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33945472","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on medical imaging","raw_type":null},{"id":"pmh:oai:arXiv.org:2106.07159","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.07159","pdf_url":"https://arxiv.org/pdf/2106.07159","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2106.07159","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.07159","pdf_url":"https://arxiv.org/pdf/2106.07159","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3621817804","display_name":null,"funder_award_id":"1703883","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3626087347","display_name":null,"funder_award_id":"1733843","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6185649808","display_name":null,"funder_award_id":"1849238","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6392561116","display_name":null,"funder_award_id":"1747778","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G862796630","display_name":null,"funder_award_id":"1763523","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1554187497","https://openalex.org/W1965744692","https://openalex.org/W2009231756","https://openalex.org/W2102605133","https://openalex.org/W2132649118","https://openalex.org/W2133147610","https://openalex.org/W2136962287","https://openalex.org/W2183389629","https://openalex.org/W2194775991","https://openalex.org/W2198296987","https://openalex.org/W2216192774","https://openalex.org/W2264784471","https://openalex.org/W2550409828","https://openalex.org/W2557889580","https://openalex.org/W2565639579","https://openalex.org/W2605482930","https://openalex.org/W2758694956","https://openalex.org/W2789926374","https://openalex.org/W2806190463","https://openalex.org/W2806530968","https://openalex.org/W2904554302","https://openalex.org/W2921092847","https://openalex.org/W2944712585","https://openalex.org/W2962676885","https://openalex.org/W2962773068","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W2963659353","https://openalex.org/W2963689087","https://openalex.org/W2963857746","https://openalex.org/W2963927307","https://openalex.org/W2964236837","https://openalex.org/W2980046504","https://openalex.org/W2980134361","https://openalex.org/W2982161360","https://openalex.org/W2989604896","https://openalex.org/W2997132074","https://openalex.org/W2999044405","https://openalex.org/W3035358681","https://openalex.org/W3110482695","https://openalex.org/W3111521801","https://openalex.org/W6620707391","https://openalex.org/W6631190155","https://openalex.org/W6639824700","https://openalex.org/W6689298463","https://openalex.org/W6697925102","https://openalex.org/W6753494528","https://openalex.org/W6760424586","https://openalex.org/W6785652829"],"related_works":[],"abstract_inverted_index":{"Instance":[0],"segmentation":[1,37,41,52,97,124,134,160],"is":[2,126],"of":[3,13,106,190],"great":[4],"importance":[5],"for":[6],"many":[7],"biological":[8,184],"applications,":[9],"such":[10],"as":[11,140],"study":[12],"neural":[14],"cell":[15],"interactions,":[16],"plant":[17],"phenotyping,":[18],"and":[19,48,81,172],"quantitatively":[20],"measuring":[21],"how":[22],"cells":[23],"react":[24],"to":[25,77,142],"drug":[26],"treatment.":[27],"In":[28],"this":[29,87,90],"paper,":[30,91],"we":[31,92,162],"propose":[32,93],"a":[33],"novel":[34],"box-based":[35],"instance":[36,40,96],"method.":[38,98,192],"Box-based":[39],"methods":[42,60],"capture":[43],"objects":[44,69],"via":[45],"bounding":[46,55,73,112,153],"boxes":[47],"then":[49,116],"perform":[50,119],"individual":[51],"within":[53,70,150],"each":[54],"box":[56,74,113,154],"region.":[57,155],"However,":[58],"existing":[59],"can":[61],"hardly":[62],"differentiate":[63],"the":[64,71,103,107,111,130,137,147,151,159,177,188],"target":[65,144],"from":[66,109,146],"its":[67],"neighboring":[68,148],"same":[72,152],"region":[75],"due":[76],"their":[78],"similar":[79],"textures":[80],"low-contrast":[82],"boundaries.":[83],"To":[84,118,156],"deal":[85],"with":[86,129],"problem,":[88],"in":[89,176],"an":[94,121,164],"object-guided":[95,122],"Our":[99],"method":[100],"first":[101],"detects":[102],"center":[104],"points":[105],"objects,":[108],"which":[110],"parameters":[114],"are":[115],"predicted.":[117],"segmentation,":[120],"coarse-to-fine":[123],"branch":[125,135],"built":[127],"along":[128],"detection":[131],"branch.":[132],"The":[133,193],"reuses":[136],"object":[138,145],"features":[139,175],"guidance":[141],"separate":[143],"ones":[149],"further":[157],"improve":[158],"quality,":[161],"design":[163],"auxiliary":[165],"feature":[166],"refinement":[167],"module":[168],"that":[169],"densely":[170],"samples":[171],"refines":[173],"point-wise":[174],"boundary":[178],"regions.":[179],"Experimental":[180],"results":[181],"on":[182],"three":[183],"image":[185],"datasets":[186],"demonstrate":[187],"advantages":[189],"our":[191],"code":[194],"will":[195],"be":[196],"available":[197],"at":[198],"https://github.com/yijingru/ObjGuided-Instance-Segmentation.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2021-05-10T00:00:00"}