{"id":"https://openalex.org/W2663426746","doi":"https://doi.org/10.1109/isbi.2017.7950599","title":"Blood vessel characterization using virtual 3D models and convolutional neural networks in fluorescence microscopy","display_name":"Blood vessel characterization using virtual 3D models and convolutional neural networks in fluorescence microscopy","publication_year":2017,"publication_date":"2017-04-01","ids":{"openalex":"https://openalex.org/W2663426746","doi":"https://doi.org/10.1109/isbi.2017.7950599","mag":"2663426746"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2017.7950599","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2017.7950599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","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/A5061701343","display_name":"Aritra Chowdhury","orcid":"https://orcid.org/0000-0002-0579-292X"},"institutions":[{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Aritra Chowdhury","raw_affiliation_strings":["GE Global Research Center, Niskayuna, NY"],"affiliations":[{"raw_affiliation_string":"GE Global Research Center, Niskayuna, NY","institution_ids":["https://openalex.org/I4210134512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031517308","display_name":"Dmitry V. Dylov","orcid":"https://orcid.org/0000-0003-2251-3221"},"institutions":[{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dmitry V. Dylov","raw_affiliation_strings":["GE Global Research Center, Niskayuna NY, United States of America"],"affiliations":[{"raw_affiliation_string":"GE Global Research Center, Niskayuna NY, United States of America","institution_ids":["https://openalex.org/I4210134512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100404176","display_name":"Qing Li","orcid":"https://orcid.org/0000-0003-3370-471X"},"institutions":[{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qing Li","raw_affiliation_strings":["GE Global Research Center, Niskayuna, NY"],"affiliations":[{"raw_affiliation_string":"GE Global Research Center, Niskayuna, NY","institution_ids":["https://openalex.org/I4210134512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055924684","display_name":"Michael B. MacDonald","orcid":"https://orcid.org/0000-0002-9083-9357"},"institutions":[{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael MacDonald","raw_affiliation_strings":["GE Global Research Center, Niskayuna, NY"],"affiliations":[{"raw_affiliation_string":"GE Global Research Center, Niskayuna, NY","institution_ids":["https://openalex.org/I4210134512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091741718","display_name":"Dan E. Meyer","orcid":"https://orcid.org/0000-0002-1574-1704"},"institutions":[{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dan E. Meyer","raw_affiliation_strings":["GE Global Research Center, Niskayuna, NY"],"affiliations":[{"raw_affiliation_string":"GE Global Research Center, Niskayuna, NY","institution_ids":["https://openalex.org/I4210134512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018951696","display_name":"Michael Marino","orcid":"https://orcid.org/0000-0001-5452-1782"},"institutions":[{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Marino","raw_affiliation_strings":["GE Global Research Center, Niskayuna, NY"],"affiliations":[{"raw_affiliation_string":"GE Global Research Center, Niskayuna, NY","institution_ids":["https://openalex.org/I4210134512"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025131969","display_name":"Alberto Santamar\u00eda-Pang","orcid":"https://orcid.org/0000-0003-4012-8394"},"institutions":[{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alberto Santamaria-Pang","raw_affiliation_strings":["GE Global Research Center, Niskayuna, NY"],"affiliations":[{"raw_affiliation_string":"GE Global Research Center, Niskayuna, NY","institution_ids":["https://openalex.org/I4210134512"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5061701343"],"corresponding_institution_ids":["https://openalex.org/I4210134512"],"apc_list":null,"apc_paid":null,"fwci":1.3652,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.85673963,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"629","last_page":"632"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9976000189781189,"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":0.9976000189781189,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9955000281333923,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9947999715805054,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7710690498352051},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6553411483764648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5986589193344116},{"id":"https://openalex.org/keywords/blood-vessel","display_name":"Blood vessel","score":0.5808747410774231},{"id":"https://openalex.org/keywords/lumen","display_name":"Lumen (anatomy)","score":0.5366513133049011},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45940083265304565},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4214860200881958},{"id":"https://openalex.org/keywords/microvessel","display_name":"Microvessel","score":0.4152575135231018},{"id":"https://openalex.org/keywords/biomedical-engineering","display_name":"Biomedical engineering","score":0.40737417340278625},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.32757335901260376},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.1864655613899231},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.10180270671844482},{"id":"https://openalex.org/keywords/immunohistochemistry","display_name":"Immunohistochemistry","score":0.0956788957118988}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7710690498352051},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6553411483764648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5986589193344116},{"id":"https://openalex.org/C2777663904","wikidata":"https://www.wikidata.org/wiki/Q988343","display_name":"Blood vessel","level":2,"score":0.5808747410774231},{"id":"https://openalex.org/C131631996","wikidata":"https://www.wikidata.org/wiki/Q1141325","display_name":"Lumen (anatomy)","level":2,"score":0.5366513133049011},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45940083265304565},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4214860200881958},{"id":"https://openalex.org/C2776436680","wikidata":"https://www.wikidata.org/wiki/Q1632335","display_name":"Microvessel","level":3,"score":0.4152575135231018},{"id":"https://openalex.org/C136229726","wikidata":"https://www.wikidata.org/wiki/Q327092","display_name":"Biomedical engineering","level":1,"score":0.40737417340278625},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.32757335901260376},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.1864655613899231},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.10180270671844482},{"id":"https://openalex.org/C204232928","wikidata":"https://www.wikidata.org/wiki/Q899285","display_name":"Immunohistochemistry","level":2,"score":0.0956788957118988},{"id":"https://openalex.org/C95444343","wikidata":"https://www.wikidata.org/wiki/Q7141","display_name":"Cell biology","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/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2017.7950599","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2017.7950599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6000000238418579,"display_name":"Life below water","id":"https://metadata.un.org/sdg/14"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2036718463","https://openalex.org/W2104276184","https://openalex.org/W2108598243","https://openalex.org/W2148143831","https://openalex.org/W4239072543","https://openalex.org/W6676297131"],"related_works":["https://openalex.org/W2767651786","https://openalex.org/W2912288872","https://openalex.org/W564581980","https://openalex.org/W2385920759","https://openalex.org/W2159546193","https://openalex.org/W2353938019","https://openalex.org/W1966095709","https://openalex.org/W1919370033","https://openalex.org/W2164936041","https://openalex.org/W2467793082"],"abstract_inverted_index":{"We":[0,158],"report":[1],"an":[2],"automated":[3],"method":[4],"for":[5,176],"characterization":[6],"of":[7,12,22,29,31,35,49,54,58,116,149,172],"microvessel":[8],"morphology":[9,57],"in":[10,62,78,108],"micrographs":[11],"brain":[13,83],"tissue":[14,84],"sections":[15],"to":[16,42,128],"enable":[17],"the":[18,56,150,165,177],"facile,":[19],"quantitative":[20],"analysis":[21,113],"vascular":[23],"differences":[24],"across":[25],"large":[26],"datasets":[27],"consisting":[28],"hundreds":[30],"images":[32],"with":[33,99],"thousands":[34],"blood":[36,87,97,104,131],"vessel":[37],"objects.":[38],"Our":[39],"objective":[40],"is":[41,126,156],"show":[43],"that":[44,73,160],"virtual":[45,151,166],"3D":[46],"parametric":[47],"models":[48,155,162],"vasculature":[50],"are":[51,74],"adequately":[52],"capable":[53],"representing":[55],"naturally":[59],"acquired":[60],"data":[61,154,167],"neuropathology.":[63],"In":[64],"this":[65],"work,":[66],"we":[67],"focus":[68],"on":[69,164],"three":[70],"distinct":[71,100],"morphologies":[72],"most":[75],"frequently":[76],"observed":[77,159],"formalin-fixed,":[79],"paraffin-embedded":[80],"(FFPE)":[81],"human":[82],"samples:":[85],"single":[86,96,130],"vessels":[88,98,105,132],"showing":[89],"no":[90],"(or":[91],"collapsed)":[92],"significant":[93],"lumen":[94,101],"(\u201cRoundLumen-\u201d);":[95],"(\u201cRoundLumen+\u201d);":[102],"two":[103,178],"bundled":[106],"together":[107],"close":[109],"proximity":[110],"(\u201cTwins\u201d).":[111],"The":[112],"involves":[114],"extraction":[115],"features":[117],"using":[118],"pre-trained":[119],"convolutional":[120],"neural":[121],"networks.":[122],"A":[123,146],"hierarchical":[124],"classification":[125,141,161,180],"performed":[127],"distinguish":[129],"(RoundLumen)":[133],"from":[134],"Twins;":[135],"followed":[136],"by":[137],"a":[138],"more":[139],"granular":[140],"between":[142],"RoundLumen-":[143],"and":[144,152,174],"RoundLumen+.":[145],"side-by-side":[147],"comparison":[148],"natural":[153],"presented.":[157],"built":[163],"perform":[168],"well":[169],"achieving":[170],"accuracies":[171],"92.8%":[173],"98.3%":[175],"aforementioned":[179],"tasks":[181],"respectively.":[182]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}