{"id":"https://openalex.org/W2998709208","doi":"https://doi.org/10.1109/dicta47822.2019.8945839","title":"EncapNet-3D and U-EncapNet for Cell Segmentation","display_name":"EncapNet-3D and U-EncapNet for Cell Segmentation","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W2998709208","doi":"https://doi.org/10.1109/dicta47822.2019.8945839","mag":"2998709208"},"language":"en","primary_location":{"id":"doi:10.1109/dicta47822.2019.8945839","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta47822.2019.8945839","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Digital Image Computing: Techniques and Applications (DICTA)","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/A5065111272","display_name":"Takumi Sato","orcid":"https://orcid.org/0000-0002-2253-149X"},"institutions":[{"id":"https://openalex.org/I96636082","display_name":"Meijo University","ror":"https://ror.org/04h42fc75","country_code":"JP","type":"education","lineage":["https://openalex.org/I96636082"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takumi Sato","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Meijo University, 1-501 Shiogamaguchi, Tempaku-ku, Nagoya, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Meijo University, 1-501 Shiogamaguchi, Tempaku-ku, Nagoya, Japan","institution_ids":["https://openalex.org/I96636082"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103163418","display_name":"Kazuhiro Hotta","orcid":"https://orcid.org/0000-0002-5675-8713"},"institutions":[{"id":"https://openalex.org/I96636082","display_name":"Meijo University","ror":"https://ror.org/04h42fc75","country_code":"JP","type":"education","lineage":["https://openalex.org/I96636082"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuhiro Hotta","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Meijo University, 1-501 Shiogamaguchi, Tempaku-ku, Nagoya, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Meijo University, 1-501 Shiogamaguchi, Tempaku-ku, Nagoya, Japan","institution_ids":["https://openalex.org/I96636082"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I96636082"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9983000159263611,"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":0.991100013256073,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.714687705039978},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7096049189567566},{"id":"https://openalex.org/keywords/connection","display_name":"Connection (principal bundle)","score":0.679236650466919},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6720297336578369},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.660675585269928},{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.6018376350402832},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.5288798809051514},{"id":"https://openalex.org/keywords/capsule","display_name":"Capsule","score":0.5021092891693115},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4650709629058838},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4629659652709961},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4468223452568054},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32357025146484375},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2426280677318573},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.18626540899276733},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16741609573364258},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12497073411941528},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.10397210717201233},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10190442204475403},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.07465225458145142}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.714687705039978},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7096049189567566},{"id":"https://openalex.org/C13355873","wikidata":"https://www.wikidata.org/wiki/Q2920850","display_name":"Connection (principal bundle)","level":2,"score":0.679236650466919},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6720297336578369},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.660675585269928},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.6018376350402832},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.5288798809051514},{"id":"https://openalex.org/C2778778583","wikidata":"https://www.wikidata.org/wiki/Q147768","display_name":"Capsule","level":2,"score":0.5021092891693115},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4650709629058838},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4629659652709961},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4468223452568054},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32357025146484375},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2426280677318573},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.18626540899276733},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16741609573364258},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12497073411941528},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.10397210717201233},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10190442204475403},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.07465225458145142},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dicta47822.2019.8945839","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta47822.2019.8945839","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1884191083","https://openalex.org/W1901129140","https://openalex.org/W2292153256","https://openalex.org/W2419448466","https://openalex.org/W2785994986","https://openalex.org/W2803218650","https://openalex.org/W2809361304","https://openalex.org/W2811344226","https://openalex.org/W2886134486","https://openalex.org/W2895526696","https://openalex.org/W2895967295","https://openalex.org/W2903024257","https://openalex.org/W2903110538","https://openalex.org/W2955268453","https://openalex.org/W2963125010","https://openalex.org/W2963499089","https://openalex.org/W2963703618","https://openalex.org/W2964079212","https://openalex.org/W3101197104","https://openalex.org/W4293406525","https://openalex.org/W4297775537","https://openalex.org/W4394560274","https://openalex.org/W6717372056","https://openalex.org/W6737664043","https://openalex.org/W6740474667","https://openalex.org/W6743446608","https://openalex.org/W6748053814","https://openalex.org/W6751575020","https://openalex.org/W6752048237","https://openalex.org/W6755474410","https://openalex.org/W6756711085"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W2885125400","https://openalex.org/W1989889224","https://openalex.org/W4382618745","https://openalex.org/W1973775000","https://openalex.org/W2748922771","https://openalex.org/W1987128138","https://openalex.org/W2743976221"],"abstract_inverted_index":{"EncapNet":[0,40],"is":[1],"a":[2],"kind":[3],"of":[4,20,110,117],"Capsule":[5],"network":[6,90],"that":[7,12,29],"significantly":[8],"improved":[9],"routing":[10],"problems":[11],"has":[13,30,41,85,114,128],"thought":[14],"to":[15,57,76,88,96],"be":[16],"the":[17,105],"main":[18],"bottleneck":[19],"capsule":[21],"network.":[22],"In":[23],"this":[24,49],"paper,":[25],"we":[26],"propose":[27,70],"EncapNet-3D":[28,84,127],"stronger":[31],"connection":[32,58,64],"between":[33,59,65],"master":[34],"and":[35,54],"aide":[36],"branch,":[37],"which":[38,72],"original":[39],"only":[42],"single":[43],"co-efficient":[44],"per":[45],"capsule.":[46],"We":[47,68,103],"achieved":[48,129],"by":[50],"adding":[51],"3D":[52,61],"convolution":[53,62],"Dropout":[55],"layers":[56],"them.":[60],"makes":[63],"capsules":[66],"stronger.":[67],"also":[69],"U-EncapNet,":[71,97],"uses":[73],"U-net":[74],"architecture":[75],"achieve":[77],"high":[78],"accuracy":[79],"in":[80,119,123,132,136],"semantic":[81],"segmentation":[82,108],"task.":[83],"successfully":[86],"accomplished":[87],"reduce":[89],"parameters":[91],"321":[92],"times":[93,99],"smaller":[94,100],"compared":[95],"52":[98],"than":[101],"U-net.":[102,126],"show":[104],"result":[106],"on":[107],"problem":[109],"cell":[111,120,137],"images.":[112],"U-EncapNet":[113],"advanced":[115],"performance":[116],"1.1%":[118],"mean":[121],"IoU":[122],"comparison":[124,133],"with":[125,134],"3%":[130],"increase":[131],"ResNet-6":[135],"membrane":[138],"IoU.":[139]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}