{"id":"https://openalex.org/W1606734834","doi":"https://doi.org/10.1109/isbi.2015.7163890","title":"A novel nested graph cuts method for segmenting human lymph nodes in 3D high frequency ultrasound images","display_name":"A novel nested graph cuts method for segmenting human lymph nodes in 3D high frequency ultrasound images","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W1606734834","doi":"https://doi.org/10.1109/isbi.2015.7163890","mag":"1606734834"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2015.7163890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2015.7163890","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)","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/A5027879759","display_name":"Jen-Wei Kuo","orcid":"https://orcid.org/0000-0001-7340-0150"},"institutions":[{"id":"https://openalex.org/I90965887","display_name":"SUNY Polytechnic Institute","ror":"https://ror.org/000fxgx19","country_code":"US","type":"education","lineage":["https://openalex.org/I90965887"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jen-wei Kuo","raw_affiliation_strings":["Department of Electrical and Computer Engineering, NYU Polytechnic School of Engineering, NY"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, NYU Polytechnic School of Engineering, NY","institution_ids":["https://openalex.org/I90965887"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076167293","display_name":"Jonathan Mamou","orcid":"https://orcid.org/0000-0002-9412-165X"},"institutions":[{"id":"https://openalex.org/I4210132419","display_name":"Riverside Research Institute","ror":"https://ror.org/02tvg0w73","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210132419"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan Mamou","raw_affiliation_strings":["F. L. Lizzi Center for Biomedical Engineering, Riverside Research, New York, NY"],"affiliations":[{"raw_affiliation_string":"F. L. Lizzi Center for Biomedical Engineering, Riverside Research, New York, NY","institution_ids":["https://openalex.org/I4210132419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100319039","display_name":"Yao Wang","orcid":"https://orcid.org/0000-0003-3199-3802"},"institutions":[{"id":"https://openalex.org/I90965887","display_name":"SUNY Polytechnic Institute","ror":"https://ror.org/000fxgx19","country_code":"US","type":"education","lineage":["https://openalex.org/I90965887"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yao Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, NYU Polytechnic School of Engineering, NY"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, NYU Polytechnic School of Engineering, NY","institution_ids":["https://openalex.org/I90965887"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029223419","display_name":"Emi Saegusa-Beecroft","orcid":null},"institutions":[{"id":"https://openalex.org/I117965899","display_name":"University of Hawai\u02bbi at M\u0101noa","ror":"https://ror.org/01wspgy28","country_code":"US","type":"education","lineage":["https://openalex.org/I117965899"]},{"id":"https://openalex.org/I1312008915","display_name":"Kuakini Medical Center","ror":"https://ror.org/002yfn631","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1312008915"]},{"id":"https://openalex.org/I1331384533","display_name":"University of Hawaii System","ror":"https://ror.org/03tzaeb71","country_code":"US","type":"education","lineage":["https://openalex.org/I1331384533"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Emi Saegusa-Beecroft","raw_affiliation_strings":["University of Hawaii and Kuakini Medical Center, Honolulu, HI"],"affiliations":[{"raw_affiliation_string":"University of Hawaii and Kuakini Medical Center, Honolulu, HI","institution_ids":["https://openalex.org/I1312008915","https://openalex.org/I117965899","https://openalex.org/I1331384533"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112213212","display_name":"Junji Machi","orcid":null},"institutions":[{"id":"https://openalex.org/I1331384533","display_name":"University of Hawaii System","ror":"https://ror.org/03tzaeb71","country_code":"US","type":"education","lineage":["https://openalex.org/I1331384533"]},{"id":"https://openalex.org/I117965899","display_name":"University of Hawai\u02bbi at M\u0101noa","ror":"https://ror.org/01wspgy28","country_code":"US","type":"education","lineage":["https://openalex.org/I117965899"]},{"id":"https://openalex.org/I1312008915","display_name":"Kuakini Medical Center","ror":"https://ror.org/002yfn631","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1312008915"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junji Machi","raw_affiliation_strings":["University of Hawaii and Kuakini Medical Center, Honolulu, HI"],"affiliations":[{"raw_affiliation_string":"University of Hawaii and Kuakini Medical Center, Honolulu, HI","institution_ids":["https://openalex.org/I1312008915","https://openalex.org/I117965899","https://openalex.org/I1331384533"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030215699","display_name":"Ernest J. Feleppa","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132419","display_name":"Riverside Research Institute","ror":"https://ror.org/02tvg0w73","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210132419"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ernest J. Feleppa","raw_affiliation_strings":["F. L. Lizzi Center for Biomedical Engineering, Riverside Research, New York, NY"],"affiliations":[{"raw_affiliation_string":"F. L. Lizzi Center for Biomedical Engineering, Riverside Research, New York, NY","institution_ids":["https://openalex.org/I4210132419"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5027879759"],"corresponding_institution_ids":["https://openalex.org/I90965887"],"apc_list":null,"apc_paid":null,"fwci":0.7364,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78022512,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"372","last_page":"375"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9943000078201294,"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":0.9943000078201294,"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/T10727","display_name":"Ultrasound Imaging and Elastography","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9904000163078308,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6921622157096863},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6586606502532959},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6535146236419678},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.520576536655426},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5122098326683044},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.50485759973526},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.48135215044021606},{"id":"https://openalex.org/keywords/attenuation","display_name":"Attenuation","score":0.47480881214141846},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4415787160396576},{"id":"https://openalex.org/keywords/ultrasound","display_name":"Ultrasound","score":0.4413905739784241},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.10933929681777954},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.0964708924293518},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08082467317581177}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6921622157096863},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6586606502532959},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6535146236419678},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.520576536655426},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5122098326683044},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.50485759973526},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.48135215044021606},{"id":"https://openalex.org/C184652730","wikidata":"https://www.wikidata.org/wiki/Q2357982","display_name":"Attenuation","level":2,"score":0.47480881214141846},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4415787160396576},{"id":"https://openalex.org/C143753070","wikidata":"https://www.wikidata.org/wiki/Q162564","display_name":"Ultrasound","level":2,"score":0.4413905739784241},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.10933929681777954},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0964708924293518},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08082467317581177},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2015.7163890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2015.7163890","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1999907661","https://openalex.org/W2085261163","https://openalex.org/W2110593503","https://openalex.org/W2119259757","https://openalex.org/W2140502500","https://openalex.org/W2169269637","https://openalex.org/W2543261561"],"related_works":["https://openalex.org/W2062605435","https://openalex.org/W2273182195","https://openalex.org/W2186374051","https://openalex.org/W2377963109","https://openalex.org/W2022279172","https://openalex.org/W2352247021","https://openalex.org/W2059332403","https://openalex.org/W2767089762","https://openalex.org/W2145835458","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Three-dimensional":[0],"(3D)":[1],"quantitative-ultrasound":[2],"(QUS)":[3],"methods":[4],"were":[5,117],"recently":[6],"developed":[7],"and":[8,38,52,96,107],"successfully":[9],"applied":[10],"to":[11,93,127],"detect":[12],"cancerous":[13],"regions":[14],"in":[15],"freshly-dissected":[16],"lymph":[17],"nodes":[18],"(LNs).":[19],"The":[20],"3D":[21],"high":[22],"frequency":[23],"ultrasound":[24],"(HFU)":[25],"images":[26],"obtained":[27],"from":[28],"these":[29],"LNs":[30],"contain":[31],"three":[32],"different":[33],"parts:":[34],"LN-parenchyma":[35],"(LNP),":[36],"fat,":[37],"phosphate-buffered":[39],"saline":[40],"(PBS).":[41],"To":[42,80],"apply":[43],"QUS":[44],"estimates":[45],"inside":[46],"the":[47,73,77,82,86,120],"LNP":[48,56,90],"region,":[49],"an":[50,101],"automatic":[51,122],"accurate":[53],"algorithm":[54,124],"for":[55],"segmentation":[57,123,130],"is":[58],"needed.":[59],"In":[60],"this":[61],"paper,":[62],"we":[63,98],"describe":[64,100],"a":[65,132],"novel,":[66],"nested-graph-cut":[67],"(NGC)":[68],"method":[69],"that":[70],"effectively":[71],"exploits":[72],"nested":[74],"structure":[75],"of":[76,85,89,115,135],"LN":[78],"images.":[79],"overcome":[81],"large":[83],"variability":[84],"intensity":[87,110],"distribution":[88],"pixels":[91],"due":[92],"acoustic":[94],"attenuation":[95],"focusing,":[97],"further":[99],"iterative":[102],"self-updating":[103],"framework":[104],"combining":[105],"NGC":[106],"spline-based":[108],"robust":[109],"fitting.":[111],"Dice":[112],"similarity":[113],"coefficients":[114],"89.56\u00b18.44%":[116],"achieved":[118],"when":[119],"proposed":[121],"was":[125],"compared":[126],"expert":[128],"manual":[129],"on":[131],"dataset":[133],"consisting":[134],"115":[136],"LNs.":[137]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
