乐胖代购免代理版

{"id":"https://openalex.org/W2122925473","doi":"https://doi.org/10.1109/tbme.2007.899310","title":"Polygonal Modeling of Contours of Breast Tumors With the Preservation of Spicules","display_name":"Polygonal Modeling of Contours of Breast Tumors With the Preservation of Spicules","publication_year":2007,"publication_date":"2007-12-20","ids":{"openalex":"https://openalex.org/W2122925473","doi":"https://doi.org/10.1109/tbme.2007.899310","mag":"2122925473","pmid":"https://pubmed.ncbi.nlm.nih.gov/18232342"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbme.2007.899310","pdf_url":null,"source":{"id":"https://openalex.org/S5240358","display_name":"IEEE Transactions on Biomedical Engineering","issn_l":"0018-9294","issn":["0018-9294","1558-2531"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"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":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5068910731","display_name":"Denise Guliato","orcid":null},"institutions":[{"id":"https://openalex.org/I80850581","display_name":"Universidade Federal de Uberl\u00e2ndia","ror":"https://ror.org/04x3wvr31","country_code":"BR","type":"funder","lineage":["https://openalex.org/I80850581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"D. Guliato","raw_affiliation_strings":["Faculdade de Computa\u00e7\u00e3o, Universidade Federal de Uberl\u00e2andia, Minas Gerais, Brazil"],"affiliations":[{"raw_affiliation_string":"Faculdade de Computa\u00e7\u00e3o, Universidade Federal de Uberl\u00e2andia, Minas Gerais, Brazil","institution_ids":["https://openalex.org/I80850581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008235253","display_name":"Rangaraj M. Rangayyan","orcid":"https://orcid.org/0000-0002-6764-8691"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"funder","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"R.M. Rangayyan","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Schulich School of Engineering, Department of Radiology, University of Calgary, Calgary, AB, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Schulich School of Engineering, Department of Radiology, University of Calgary, Calgary, AB, Canada","institution_ids":["https://openalex.org/I168635309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058402630","display_name":"Juliano Daloia de Carvalho","orcid":null},"institutions":[{"id":"https://openalex.org/I80850581","display_name":"Universidade Federal de Uberl\u00e2ndia","ror":"https://ror.org/04x3wvr31","country_code":"BR","type":"funder","lineage":["https://openalex.org/I80850581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"J.D. Carvalho","raw_affiliation_strings":["Faculdade de Computa\u00e7\u00e3o, Universidade Federal de Uberl\u00e2andia, Minas Gerais, Brazil"],"affiliations":[{"raw_affiliation_string":"Faculdade de Computa\u00e7\u00e3o, Universidade Federal de Uberl\u00e2andia, Minas Gerais, Brazil","institution_ids":["https://openalex.org/I80850581"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041528846","display_name":"S\u00e9rgio A. Santiago","orcid":null},"institutions":[{"id":"https://openalex.org/I80850581","display_name":"Universidade Federal de Uberl\u00e2ndia","ror":"https://ror.org/04x3wvr31","country_code":"BR","type":"funder","lineage":["https://openalex.org/I80850581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"S.A. Santiago","raw_affiliation_strings":["Faculdade de Computa\u00e7\u00e3o, Universidade Federal de Uberl\u00e2andia, Minas Gerais, Brazil"],"affiliations":[{"raw_affiliation_string":"Faculdade de Computa\u00e7\u00e3o, Universidade Federal de Uberl\u00e2andia, Minas Gerais, Brazil","institution_ids":["https://openalex.org/I80850581"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.62,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":59,"citation_normalized_percentile":{"value":0.963198,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":95},"biblio":{"volume":"55","issue":"1","first_page":"14","last_page":"20"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9984,"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":"AI in cancer detection","score":0.9984,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9907,"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":0.9869,"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/breast-tumor","display_name":"Breast tumor","score":0.44697556}],"concepts":[{"id":"https://openalex.org/C96618477","wikidata":"https://www.wikidata.org/wiki/Q520831","display_name":"Sponge spicule","level":2,"score":0.5935338},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.57898664},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.5627663},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49868727},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4605294},{"id":"https://openalex.org/C2986637895","wikidata":"https://www.wikidata.org/wiki/Q953865","display_name":"Breast tumor","level":4,"score":0.44697556},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.445567},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42645362},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40429774},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39450663},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.21332243},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.15604511},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.1291559},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11487004},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.09694472},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.08525714},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":"","qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001943","descriptor_name":"Breast Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D008327","descriptor_name":"Mammography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008954","descriptor_name":"Models, Biological","qualifier_ui":"","qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D011856","descriptor_name":"Radiographic Image Enhancement","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D011857","descriptor_name":"Radiographic Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D001943","descriptor_name":"Breast Neoplasms","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008327","descriptor_name":"Mammography","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011856","descriptor_name":"Radiographic Image Enhancement","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011857","descriptor_name":"Radiographic Image Interpretation, Computer-Assisted","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":"","qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbme.2007.899310","pdf_url":null,"source":{"id":"https://openalex.org/S5240358","display_name":"IEEE Transactions on Biomedical Engineering","issn_l":"0018-9294","issn":["0018-9294","1558-2531"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"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":null,"is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/18232342","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_indexed_in_scopus":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":["National Institutes of Health"],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41,"id":"https://metadata.un.org/sdg/15","display_name":"Life on land"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":42,"referenced_works":["https://openalex.org/W134425850","https://openalex.org/W1508951912","https://openalex.org/W1553171952","https://openalex.org/W1967415082","https://openalex.org/W1968114652","https://openalex.org/W1971825032","https://openalex.org/W1974536055","https://openalex.org/W1975855047","https://openalex.org/W1979819178","https://openalex.org/W1982819904","https://openalex.org/W1984238580","https://openalex.org/W1996015349","https://openalex.org/W2004594863","https://openalex.org/W2010952951","https://openalex.org/W2017074421","https://openalex.org/W2026506545","https://openalex.org/W2031136835","https://openalex.org/W2034254304","https://openalex.org/W2038952578","https://openalex.org/W2043735243","https://openalex.org/W2047755713","https://openalex.org/W2059331675","https://openalex.org/W2065358322","https://openalex.org/W2067485484","https://openalex.org/W2071867759","https://openalex.org/W2074613519","https://openalex.org/W2086921140","https://openalex.org/W2107691243","https://openalex.org/W2108206973","https://openalex.org/W2108940541","https://openalex.org/W2112241148","https://openalex.org/W2114097597","https://openalex.org/W2128282196","https://openalex.org/W2129597286","https://openalex.org/W2144647583","https://openalex.org/W2149152304","https://openalex.org/W2155195832","https://openalex.org/W2514575318","https://openalex.org/W2913525866","https://openalex.org/W4205944311","https://openalex.org/W4249058857","https://openalex.org/W4255333169"],"related_works":["https://openalex.org/W67063621","https://openalex.org/W2753204287","https://openalex.org/W2598299700","https://openalex.org/W2472014349","https://openalex.org/W2392223909","https://openalex.org/W2380970850","https://openalex.org/W2379978292","https://openalex.org/W2354843413","https://openalex.org/W2155071509","https://openalex.org/W2100449780"],"abstract_inverted_index":{"Malignant":[0],"breast":[1],"tumors":[2,44],"typically":[3],"appear":[4],"in":[5,40,150],"mammograms":[6],"with":[7,130],"rough,":[8],"spiculated,":[9],"or":[10,21],"microlobulated":[11],"contours,":[12],"whereas":[13],"most":[14],"benign":[15,46,138],"masses":[16,47,139],"have":[17,26],"smooth,":[18],"round,":[19],"oval,":[20],"macrolobulated":[22],"contours.":[23],"Several":[24],"studies":[25],"shown":[27],"that":[28,31,83,93],"shape":[29],"factors":[30],"incorporate":[32],"differences":[33],"as":[34,59],"above":[35],"can":[36],"provide":[37],"high":[38,145],"accuracies":[39],"distinguishing":[41],"between":[42],"malignant":[43,142],"and":[45,71,86,140],"based":[48,68],"upon":[49,69],"their":[50],"contours":[51,82,135],"only.":[52],"However,":[53],"global":[54],"measures":[55],"of":[56,81,88,96,103,133,136,148,152],"roughness,":[57],"such":[58],"compactness,":[60],"are":[61],"less":[62],"effective":[63],"than":[64,116],"specially":[65],"designed":[66],"features":[67],"spicularity":[70],"concavity.":[72],"We":[73,91],"propose":[74],"a":[75,117,122,131],"method":[76,111],"to":[77],"derive":[78],"polygonal":[79,105],"models":[80,106],"preserve":[84],"spicules":[85],"details":[87],"diagnostic":[89],"importance.":[90],"show":[92],"an":[94],"index":[95],"spiculation":[97],"derived":[98,120],"from":[99],"the":[100,104,109,153,156],"turning":[101],"functions":[102],"obtained":[107],"by":[108],"proposed":[110],"yields":[112],"better":[113],"classification":[114,146],"accuracy":[115,147],"similar":[118],"measure":[119],"using":[121],"previously":[123],"published":[124],"method.":[125],"The":[126],"methods":[127],"were":[128],"tested":[129],"set":[132],"111":[134],"65":[137],"46":[141],"tumors.":[143],"A":[144],"0.94":[149],"terms":[151],"area":[154],"under":[155],"receiver":[157],"operating":[158],"characteristics":[159],"curve":[160],"was":[161],"obtained.":[162]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2122925473","counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":6}],"updated_date":"2025-02-21T23:41:14.435182","created_date":"2016-06-24"}