{"id":"https://openalex.org/W3186742890","doi":"https://doi.org/10.23919/date51398.2021.9474153","title":"Morphable Convolutional Neural Network for Biomedical Image Segmentation","display_name":"Morphable Convolutional Neural Network for Biomedical Image Segmentation","publication_year":2021,"publication_date":"2021-02-01","ids":{"openalex":"https://openalex.org/W3186742890","doi":"https://doi.org/10.23919/date51398.2021.9474153","mag":"3186742890"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.23919/date51398.2021.9474153","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","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/A5071846463","display_name":"Huaipan Jiang","orcid":"https://orcid.org/0000-0002-8160-1611"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huaipan Jiang","raw_affiliation_strings":["The Pennsylvania State University, University Park, PA"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, University Park, PA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067815274","display_name":"Anup Sarma","orcid":"https://orcid.org/0000-0002-0098-4498"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anup Sarma","raw_affiliation_strings":["The Pennsylvania State University, University Park, PA"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, University Park, PA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045491562","display_name":"Mengran Fan","orcid":"https://orcid.org/0000-0002-5352-8568"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mengran Fan","raw_affiliation_strings":["The Pennsylvania State University, University Park, PA"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, University Park, PA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013480171","display_name":"Jihyun Ryoo","orcid":"https://orcid.org/0000-0002-9116-8452"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jihyun Ryoo","raw_affiliation_strings":["The Pennsylvania State University, University Park, PA"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, University Park, PA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071711630","display_name":"Meenakshi Arunachalam","orcid":null},"institutions":[{"id":"https://openalex.org/I4210158342","display_name":"Intel (United Kingdom)","ror":"https://ror.org/058cxws58","country_code":"GB","type":"company","lineage":["https://openalex.org/I1343180700","https://openalex.org/I4210158342"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Meenakshi Arunachalam","raw_affiliation_strings":["Intel"],"affiliations":[{"raw_affiliation_string":"Intel","institution_ids":["https://openalex.org/I4210158342"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103989990","display_name":"Sharada Naveen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210158342","display_name":"Intel (United Kingdom)","ror":"https://ror.org/058cxws58","country_code":"GB","type":"company","lineage":["https://openalex.org/I1343180700","https://openalex.org/I4210158342"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sharada Naveen","raw_affiliation_strings":["Intel"],"affiliations":[{"raw_affiliation_string":"Intel","institution_ids":["https://openalex.org/I4210158342"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007116603","display_name":"Mahmut Kandemir","orcid":"https://orcid.org/0000-0002-9940-9951"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mahmut T. Kandemir","raw_affiliation_strings":["The Pennsylvania State University, University Park, PA"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, University Park, PA","institution_ids":["https://openalex.org/I130769515"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.084,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.311389,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":58,"max":68},"biblio":{"volume":"9","issue":null,"first_page":"1522","last_page":"1525"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"Deep Learning in Medical Image Analysis","score":0.9992,"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"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"Deep Learning in Medical Image Analysis","score":0.9992,"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/T12859","display_name":"Advanced Techniques in Bioimage Analysis and Microscopy","score":0.999,"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":"Deep Learning in Computer Vision and Image Recognition","score":0.9989,"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/convolution","display_name":"Convolution (computer science)","score":0.6604074},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5974512},{"id":"https://openalex.org/keywords/neuronal-morphology","display_name":"Neuronal Morphology","score":0.585709},{"id":"https://openalex.org/keywords/cellular-imaging","display_name":"Cellular Imaging","score":0.540291},{"id":"https://openalex.org/keywords/phenotypic-profiling","display_name":"Phenotypic Profiling","score":0.526317},{"id":"https://openalex.org/keywords/semantic-segmentation","display_name":"Semantic Segmentation","score":0.526096},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object Detection","score":0.523128}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.81998205},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.70819837},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.66437465},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6604074},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6107045},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5974512},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5726931},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5289103},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.51159483},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.48384514},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4797717},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.44744095},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4315924},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37761533},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.24815395},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.14161578},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.23919/date51398.2021.9474153","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[{"funder":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation","award_id":"1629915,1629129,1763681,2008398"},{"funder":"https://openalex.org/F4320307102","funder_display_name":"Intel Corporation","award_id":null}],"datasets":[],"versions":[],"referenced_works_count":33,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1910657905","https://openalex.org/W1969013163","https://openalex.org/W2033663049","https://openalex.org/W2106033751","https://openalex.org/W2127218421","https://openalex.org/W2141273399","https://openalex.org/W2145023731","https://openalex.org/W2152632881","https://openalex.org/W2155893237","https://openalex.org/W2157979199","https://openalex.org/W2167510172","https://openalex.org/W2414372621","https://openalex.org/W2464708700","https://openalex.org/W2488907440","https://openalex.org/W2525090041","https://openalex.org/W2560622558","https://openalex.org/W2566989475","https://openalex.org/W2613718673","https://openalex.org/W2758694956","https://openalex.org/W2914318243","https://openalex.org/W2963150697","https://openalex.org/W2963307106","https://openalex.org/W2983581636","https://openalex.org/W3003623648","https://openalex.org/W3100296314","https://openalex.org/W3111521801","https://openalex.org/W4241071816","https://openalex.org/W4250533120","https://openalex.org/W4285719527","https://openalex.org/W593664932","https://openalex.org/W639708223"],"related_works":["https://openalex.org/W4390494008","https://openalex.org/W4293226380","https://openalex.org/W4285411112","https://openalex.org/W3135697610","https://openalex.org/W2964954556","https://openalex.org/W2922442631","https://openalex.org/W2171299904","https://openalex.org/W2085033728","https://openalex.org/W2053596378","https://openalex.org/W1647606319"],"abstract_inverted_index":{"We":[0,116],"propose":[1],"a":[2,25,56,79,90,106],"morphable":[3,70],"convolution":[4,71,99],"framework,":[5,81],"which":[6,82],"can":[7],"be":[8,102],"applied":[9],"to":[10,55,101,149],"irregularly":[11],"shaped":[12],"region":[13],"of":[14,24,32,69,110,146],"input":[15],"feature":[16,114],"map.":[17,93,115],"This":[18],"framework":[19,119,132],"reduces":[20],"the":[21,30,67,73,85,98,113,126,150],"computational":[22],"footprint":[23],"regular":[26],"CNN":[27,39,153],"operation":[28,100],"in":[29,78,112],"context":[31],"biomedical":[33],"semantic":[34],"image":[35],"segmentation.":[36],"The":[37,94],"traditional":[38],"based":[40,60],"approach":[41],"has":[42],"high":[43,48],"accuracy,":[44,147],"but":[45],"suffers":[46],"from":[47],"training":[49],"and":[50,87,125,135,141],"inference":[51],"computation":[52],"costs,":[53],"compared":[54,148],"conventional":[57,152],"edge":[58,74],"detection":[59,75],"approach.":[61],"In":[62],"this":[63],"work,":[64],"we":[65],"combine":[66],"concept":[68],"with":[72],"algorithms":[76],"resulting":[77],"hierarchical":[80],"first":[83],"detects":[84],"edges":[86],"then":[88],"generate":[89],"layer-wise":[91],"annotation":[92,95],"map":[96],"guides":[97],"run":[103],"only":[104],"on":[105,120,139],"small,":[107],"useful":[108],"fraction":[109],"pixels":[111],"evaluate":[117],"our":[118,131],"three":[121],"cell":[122],"tracking":[123],"datasets":[124],"experimental":[127],"results":[128],"indicate":[129],"that":[130],"saves":[133],"~30%":[134],"~10%":[136],"execution":[137],"time":[138],"CPU":[140],"GPU,":[142],"respectively,":[143],"without":[144],"loss":[145],"baseline":[151],"approaches.":[154]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3186742890","counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2024-10-08T11:13:16.635454","created_date":"2021-08-02"}
