{"id":"https://openalex.org/W1983309556","doi":"https://doi.org/10.1109/tro.2015.2402531","title":"Methods to Segment Hard Inclusions in Soft Tissue During Autonomous Robotic Palpation","display_name":"Methods to Segment Hard Inclusions in Soft Tissue During Autonomous Robotic Palpation","publication_year":2015,"publication_date":"2015-03-04","ids":{"openalex":"https://openalex.org/W1983309556","doi":"https://doi.org/10.1109/tro.2015.2402531","mag":"1983309556"},"language":"en","primary_location":{"id":"doi:10.1109/tro.2015.2402531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tro.2015.2402531","pdf_url":null,"source":{"id":"https://openalex.org/S144620930","display_name":"IEEE Transactions on Robotics","issn_l":"1552-3098","issn":["1552-3098","1941-0468"],"is_oa":false,"is_in_doaj":false,"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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Robotics","raw_type":"journal-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/A5081321734","display_name":"Kirk A. Nichols","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kirk A. Nichols","raw_affiliation_strings":["Department of Mechanical Engineering, Stanford University, Stanford, CA, USA","Department of Mechanical Engineering, Stanford University, Stanford, CA,#N#USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Department of Mechanical Engineering, Stanford University, Stanford, CA,#N#USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067958710","display_name":"Allison M. Okamura","orcid":"https://orcid.org/0000-0002-6912-1666"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Allison M. Okamura","raw_affiliation_strings":["Department of Mechanical Engineering, Stanford University, Stanford, CA, USA","Department of Mechanical Engineering, Stanford University, Stanford, CA,#N#USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Department of Mechanical Engineering, Stanford University, Stanford, CA,#N#USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081321734"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":3.8199,"has_fulltext":false,"cited_by_count":76,"citation_normalized_percentile":{"value":0.9320356,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"31","issue":"2","first_page":"344","last_page":"354"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9932000041007996,"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/T11984","display_name":"Anatomy and Medical Technology","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7130857706069946},{"id":"https://openalex.org/keywords/palpation","display_name":"Palpation","score":0.669848620891571},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5415776371955872},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.528449296951294},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5041846036911011},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.501270055770874},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.46487095952033997},{"id":"https://openalex.org/keywords/elastography","display_name":"Elastography","score":0.4593814015388489},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44197288155555725},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.423984557390213},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38764870166778564},{"id":"https://openalex.org/keywords/ultrasound","display_name":"Ultrasound","score":0.1562381088733673},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.12180417776107788},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.11623424291610718}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7130857706069946},{"id":"https://openalex.org/C2781167935","wikidata":"https://www.wikidata.org/wiki/Q795090","display_name":"Palpation","level":2,"score":0.669848620891571},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5415776371955872},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.528449296951294},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5041846036911011},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.501270055770874},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.46487095952033997},{"id":"https://openalex.org/C2777690781","wikidata":"https://www.wikidata.org/wiki/Q1324974","display_name":"Elastography","level":3,"score":0.4593814015388489},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44197288155555725},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.423984557390213},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38764870166778564},{"id":"https://openalex.org/C143753070","wikidata":"https://www.wikidata.org/wiki/Q162564","display_name":"Ultrasound","level":2,"score":0.1562381088733673},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.12180417776107788},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.11623424291610718},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tro.2015.2402531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tro.2015.2402531","pdf_url":null,"source":{"id":"https://openalex.org/S144620930","display_name":"IEEE Transactions on Robotics","issn_l":"1552-3098","issn":["1552-3098","1941-0468"],"is_oa":false,"is_in_doaj":false,"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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Robotics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G3203803709","display_name":null,"funder_award_id":"1227406","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1651266332","https://openalex.org/W1966418027","https://openalex.org/W1974915238","https://openalex.org/W1982261161","https://openalex.org/W1986339804","https://openalex.org/W2004510158","https://openalex.org/W2010391163","https://openalex.org/W2020434147","https://openalex.org/W2022057201","https://openalex.org/W2030329687","https://openalex.org/W2032228491","https://openalex.org/W2036754385","https://openalex.org/W2047360037","https://openalex.org/W2048613709","https://openalex.org/W2049577501","https://openalex.org/W2053179102","https://openalex.org/W2086731368","https://openalex.org/W2097038757","https://openalex.org/W2101187464","https://openalex.org/W2108584285","https://openalex.org/W2116531017","https://openalex.org/W2117345577","https://openalex.org/W2131450700","https://openalex.org/W2136885990","https://openalex.org/W2138652678","https://openalex.org/W2140678955","https://openalex.org/W2144787674","https://openalex.org/W2147462102","https://openalex.org/W2148409775","https://openalex.org/W2150654863","https://openalex.org/W2157238234","https://openalex.org/W2161698442","https://openalex.org/W2164710647","https://openalex.org/W3150683388","https://openalex.org/W4213262319","https://openalex.org/W4251957920","https://openalex.org/W6675088816"],"related_works":["https://openalex.org/W2396260350","https://openalex.org/W1481335984","https://openalex.org/W2323625407","https://openalex.org/W1503243521","https://openalex.org/W2627174696","https://openalex.org/W2417898593","https://openalex.org/W4404388673","https://openalex.org/W638052727","https://openalex.org/W2068818069","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Localizing":[0],"tumors":[1],"and":[2,12,32,134,150],"measuring":[3],"tissue":[4,54],"mechanical":[5,30],"properties":[6],"can":[7],"aid":[8],"in":[9,37,63],"surgical":[10],"planning":[11],"evaluating":[13],"the":[14,45,64,96,120,123,135],"progression":[15],"of":[16,34,53,95,122],"disease.":[17],"In":[18],"this":[19,111],"paper,":[20],"autonomous":[21,79],"robotic":[22,80],"palpation":[23],"with":[24,105,128],"supervised":[25],"machine":[26],"learning":[27,46],"algorithms":[28],"enables":[29],"localization":[31],"segmentation":[33],"stiff":[35],"inclusions":[36],"artificial":[38],"tissue.":[39,101],"Elastography":[40],"generates":[41],"training":[42],"data":[43],"for":[44],"algorithms,":[47],"providing":[48],"a":[49,71,143],"noninvasive,":[50],"inclusion-specific":[51],"characterization":[52],"mechanics.":[55],"Once":[56],"an":[57],"embedded":[58],"hard":[59],"inclusion":[60,97,131],"was":[61,84,147,152],"identified":[62],"elastographic":[65],"image,":[66],"Gaussian":[67],"discriminant":[68],"analysis":[69],"generated":[70],"classifier":[72,83,113,137],"to":[73,87,117,130],"threshold":[74],"stiffness":[75],"values":[76],"acquired":[77,90],"from":[78],"palpation.":[81],"This":[82],"later":[85],"used":[86],"classify":[88],"newly":[89],"points":[91],"as":[92],"either":[93],"part":[94],"or":[98],"surrounding":[99],"soft":[100],"An":[102],"expectation-maximization":[103],"algorithm":[104],"underlying":[106],"Markov":[107],"random":[108],"fields":[109],"improved":[110],"initial":[112,136],"over":[114],"successive":[115],"iterations":[116],"better":[118],"approximate":[119],"boundary":[121],"inclusion.":[124],"Results":[125],"demonstrate":[126],"robustness":[127],"respect":[129],"shape,":[132],"size,":[133],"value.":[138],"For":[139],"three":[140],"trials":[141],"segmenting":[142],"cubic":[144],"inclusion,":[145],"sensitivity":[146],"above":[148,153],"0.95":[149],"specificity":[151],"0.92.":[154]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":3}],"updated_date":"2026-04-24T08:23:43.765630","created_date":"2025-10-10T00:00:00"}
