{"id":"https://openalex.org/W4308233895","doi":"https://doi.org/10.1109/icip46576.2022.9897649","title":"F2RNET: A Full-Resolution Representation Network for Biomedical Image Segmentation","display_name":"F2RNET: A Full-Resolution Representation Network for Biomedical Image Segmentation","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4308233895","doi":"https://doi.org/10.1109/icip46576.2022.9897649"},"language":"en","primary_location":{"id":"doi:10.1109/icip46576.2022.9897649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897649","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"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/A5024180326","display_name":"Junlong Cheng","orcid":"https://orcid.org/0000-0002-6849-9093"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junlong Cheng","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China,610065"],"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China,610065","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066363185","display_name":"Chengrui Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengrui Gao","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China,610065"],"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China,610065","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108308972","display_name":"Changlin Li","orcid":"https://orcid.org/0000-0002-0793-0230"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changlin Li","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China,610065"],"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China,610065","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029299398","display_name":"Zhangqiang Ming","orcid":"https://orcid.org/0000-0003-1616-8054"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhangqiang Ming","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China,610065"],"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China,610065","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111595030","display_name":"Yong Yang","orcid":"https://orcid.org/0000-0002-9831-8783"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Yang","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China,610065"],"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China,610065","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103156716","display_name":"Fengjie Wang","orcid":"https://orcid.org/0000-0002-5198-8800"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengjie Wang","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China,610065"],"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China,610065","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100577418","display_name":"Min Zhu","orcid":"https://orcid.org/0009-0009-4554-7337"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Zhu","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China,610065"],"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China,610065","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5024180326"],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10387851,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"abs/2102.04306","issue":null,"first_page":"2406","last_page":"2410"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9991999864578247,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9984999895095825,"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/computer-science","display_name":"Computer science","score":0.7923730611801147},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7383673787117004},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7203229069709778},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6810493469238281},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6346432566642761},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5775390863418579},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5772342681884766},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5691841840744019},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5404729247093201},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5083124041557312},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4713838994503021},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4576297402381897},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.440538614988327},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.43200886249542236},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42279693484306335},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4208296835422516},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.085049569606781}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7923730611801147},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7383673787117004},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7203229069709778},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6810493469238281},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6346432566642761},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5775390863418579},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5772342681884766},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5691841840744019},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5404729247093201},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5083124041557312},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4713838994503021},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4576297402381897},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.440538614988327},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.43200886249542236},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42279693484306335},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4208296835422516},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.085049569606781},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip46576.2022.9897649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897649","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","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":25,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2097117768","https://openalex.org/W2618677231","https://openalex.org/W2630837129","https://openalex.org/W2803575519","https://openalex.org/W2884436604","https://openalex.org/W2907750714","https://openalex.org/W2963420686","https://openalex.org/W3025800305","https://openalex.org/W3034144495","https://openalex.org/W3092052974","https://openalex.org/W3092462072","https://openalex.org/W3094502228","https://openalex.org/W3111255625","https://openalex.org/W3127751679","https://openalex.org/W3200379731","https://openalex.org/W3213964222","https://openalex.org/W3214171258","https://openalex.org/W3216717225","https://openalex.org/W4200015473","https://openalex.org/W4294226146","https://openalex.org/W4321232185","https://openalex.org/W6748775820","https://openalex.org/W6784333009","https://openalex.org/W6790275670"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2082756648","https://openalex.org/W3194278305","https://openalex.org/W2289648981","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W2964954556"],"abstract_inverted_index":{"In":[0,86],"this":[1,137],"paper,":[2],"we":[3,88],"are":[4],"interested":[5],"in":[6,36,54,103],"exploring":[7],"the":[8,15,27,78,110,127,155],"problem":[9],"of":[10,33],"full-resolution":[11,20,106,159],"image":[12,30,116,147],"segmentation,":[13],"with":[14],"focus":[16],"placed":[17],"on":[18,113,158],"learning":[19,130],"representations":[21],"for":[22,67,77,154],"biomedicine":[23],"images.":[24],"We":[25,108],"divide":[26],"original":[28],"resolution":[29],"into":[31],"patches":[32,48,72],"different":[34,37,114],"sizes":[35],"stages":[38],"and":[39,51,92,119,149],"then":[40],"extracte":[41],"local":[42],"features":[43],"from":[44,96],"large":[45],"to":[46,75,126,145],"small":[47],"using":[49],"efficient":[50],"flexible":[52],"components":[53],"modern":[55],"convolutional":[56],"neural":[57],"networks":[58],"(CNN).":[59],"Meanwhile,":[60],"a":[61,104,122,142],"multilayer":[62],"perceptron":[63],"(MLP)":[64],"block":[65],"intended":[66],"modeling":[68],"long-range":[69],"dependencies":[70],"between":[71],"is":[73,134],"designed":[74],"compensate":[76],"inherent":[79],"inductive":[80],"bias":[81],"caused":[82],"by":[83],"convolution":[84],"operations.":[85],"addition,":[87],"perform":[89],"multi-scale":[90],"fusion":[91],"receive":[93],"representation":[94],"information":[95],"parallel":[97],"paths":[98],"at":[99],"each":[100],"stage,":[101],"resulting":[102],"rich":[105],"representation.":[107,160],"evaluate":[109],"proposed":[111],"method":[112,138],"biomedical":[115,146],"segmentation":[117,131,148],"tasks":[118],"it":[120],"achieves":[121],"competitive":[123],"performance":[124],"compared":[125],"latest":[128],"deep":[129],"methods.":[132],"It":[133],"hoped":[135],"that":[136],"will":[139],"serve":[140],"as":[141],"useful":[143],"alternative":[144],"provide":[150],"an":[151],"improved":[152],"idea":[153],"research":[156],"based":[157]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}