{"id":"https://openalex.org/W3082958208","doi":"https://doi.org/10.1109/embc44109.2020.9175846","title":"Receptive Field Size as a Key Design Parameter for Ultrasound Image Segmentation with U-Net","display_name":"Receptive Field Size as a Key Design Parameter for Ultrasound Image Segmentation with U-Net","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3082958208","doi":"https://doi.org/10.1109/embc44109.2020.9175846","mag":"3082958208","pmid":"https://pubmed.ncbi.nlm.nih.gov/33018424"},"language":"en","primary_location":{"id":"doi:10.1109/embc44109.2020.9175846","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc44109.2020.9175846","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5044445645","display_name":"Bahareh Behboodi","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Bahareh Behboodi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Concordia University, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia University, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024936964","display_name":"Maryse Fortin","orcid":"https://orcid.org/0000-0002-1189-3591"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Maryse Fortin","raw_affiliation_strings":["Department of Health, Concordia University, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Health, Concordia University, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083335682","display_name":"Clyde Belasso","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Clyde J. Belasso","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Concordia University, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia University, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035948739","display_name":"Rupert Brooks","orcid":"https://orcid.org/0000-0002-5642-7770"},"institutions":[{"id":"https://openalex.org/I4210107622","display_name":"Nuance Communications (Canada)","ror":"https://ror.org/01pshz178","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210107622","https://openalex.org/I4210125787"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Rupert Brooks","raw_affiliation_strings":["Nuance Communications Inc, Canada"],"affiliations":[{"raw_affiliation_string":"Nuance Communications Inc, Canada","institution_ids":["https://openalex.org/I4210107622"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077743201","display_name":"Hassan Rivaz","orcid":"https://orcid.org/0000-0001-5800-3034"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hassan Rivaz","raw_affiliation_strings":["Department of Electrical and Computer Engineering and PERFORM Center, Concordia University, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and PERFORM Center, Concordia University, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5044445645"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":0.3908,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.61806816,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"2020","issue":null,"first_page":"2117","last_page":"2120"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9980999827384949,"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":0.9980999827384949,"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/T10862","display_name":"AI in cancer detection","score":0.9972000122070312,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9961000084877014,"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/segmentation","display_name":"Segmentation","score":0.7838194966316223},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7696675658226013},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7518295049667358},{"id":"https://openalex.org/keywords/receptive-field","display_name":"Receptive field","score":0.7434260249137878},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6196122169494629},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5744504928588867},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5485358238220215},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5410377979278564},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.539638102054596},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5090979933738708},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4901324212551117},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.47891485691070557},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4698905944824219},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4620382785797119},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.4499616324901581},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38518449664115906},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.35785040259361267},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10532760620117188},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06075027585029602}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7838194966316223},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7696675658226013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7518295049667358},{"id":"https://openalex.org/C19071747","wikidata":"https://www.wikidata.org/wiki/Q1755207","display_name":"Receptive field","level":2,"score":0.7434260249137878},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6196122169494629},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5744504928588867},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5485358238220215},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5410377979278564},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.539638102054596},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5090979933738708},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4901324212551117},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.47891485691070557},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4698905944824219},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4620382785797119},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.4499616324901581},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38518449664115906},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35785040259361267},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10532760620117188},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06075027585029602},{"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D014463","descriptor_name":"Ultrasonography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014463","descriptor_name":"Ultrasonography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014463","descriptor_name":"Ultrasonography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc44109.2020.9175846","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc44109.2020.9175846","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:33018424","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33018424","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":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","score":0.6899999976158142,"display_name":"No poverty"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1677182931","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2119249988","https://openalex.org/W2556967412","https://openalex.org/W2774320778","https://openalex.org/W2798122215","https://openalex.org/W2893801697","https://openalex.org/W2913559493","https://openalex.org/W2936835627","https://openalex.org/W2949846184","https://openalex.org/W2963840672","https://openalex.org/W2963881378","https://openalex.org/W2964121744","https://openalex.org/W2969913432","https://openalex.org/W3021454079","https://openalex.org/W3026847561","https://openalex.org/W6631190155","https://openalex.org/W6639824700","https://openalex.org/W6696085341","https://openalex.org/W6729983426","https://openalex.org/W6750469568","https://openalex.org/W6761320662","https://openalex.org/W6767433472"],"related_works":["https://openalex.org/W1669643531","https://openalex.org/W2069711651","https://openalex.org/W2117664411","https://openalex.org/W2117933325","https://openalex.org/W1967061043","https://openalex.org/W2739874619","https://openalex.org/W2159066190","https://openalex.org/W2171698391","https://openalex.org/W2558375057","https://openalex.org/W2045480779"],"abstract_inverted_index":{"Automatic":[0],"and":[1,23,68],"accurate":[2],"segmentation":[3,50,53],"of":[4,16,26,37,54,59,103,113],"medical":[5],"images":[6],"is":[7,30],"an":[8],"important":[9],"task":[10,66],"due":[11,33],"to":[12,34,96],"the":[13,35,60,83,92,97,101,111,114],"direct":[14],"impact":[15],"this":[17,78],"procedure":[18],"on":[19],"both":[20],"disease":[21],"diagnosis":[22],"treatment.":[24],"Segmentation":[25],"ultrasound":[27],"(US)":[28],"imaging":[29],"particularly":[31],"challenging":[32],"presence":[36],"speckle":[38],"noise.":[39],"Recent":[40],"deep":[41,118],"learning":[42],"approaches":[43],"have":[44],"demonstrated":[45],"remarkable":[46],"findings":[47],"in":[48,91],"image":[49],"tasks,":[51],"including":[52],"US":[55],"images.":[56],"However,":[57],"many":[58],"newly":[61],"proposed":[62],"structures":[63],"are":[64,74],"either":[65],"specific":[67],"suffer":[69],"from":[70],"poor":[71],"generalization,":[72],"or":[73,100],"computationally":[75],"expensive.":[76],"In":[77],"paper,":[79],"we":[80],"show":[81,107],"that":[82,108],"receptive":[84,115],"field":[85],"plays":[86],"a":[87,117,125],"more":[88],"significant":[89],"role":[90],"network's":[93,98],"performance":[94],"compared":[95],"depth":[99],"number":[102],"parameters.":[104],"We":[105],"further":[106],"by":[109,124],"controlling":[110],"size":[112],"field,":[116],"network":[119],"can":[120],"instead":[121],"be":[122],"replaced":[123],"shallow":[126],"network.":[127]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}