{"id":"https://openalex.org/W2059303940","doi":"https://doi.org/10.1117/12.2082064","title":"A circumscribing active contour model for delineation of nuclei and membranes of megakaryocytes in bone marrow trephine biopsy images","display_name":"A circumscribing active contour model for delineation of nuclei and membranes of megakaryocytes in bone marrow trephine biopsy images","publication_year":2015,"publication_date":"2015-03-19","ids":{"openalex":"https://openalex.org/W2059303940","doi":"https://doi.org/10.1117/12.2082064","mag":"2059303940"},"language":"en","primary_location":{"id":"doi:10.1117/12.2082064","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2082064","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","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/A5036968205","display_name":"Tzu\u2010Hsi Song","orcid":"https://orcid.org/0000-0002-3670-8970"},"institutions":[{"id":"https://openalex.org/I39555362","display_name":"University of Warwick","ror":"https://ror.org/01a77tt86","country_code":"GB","type":"education","lineage":["https://openalex.org/I39555362"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Tzu-Hsi Song","raw_affiliation_strings":["The Univ. of Warwick (United Kingdom)","The University of Warwick, United Kingdom"],"affiliations":[{"raw_affiliation_string":"The Univ. of Warwick (United Kingdom)","institution_ids":["https://openalex.org/I39555362"]},{"raw_affiliation_string":"The University of Warwick, United Kingdom","institution_ids":["https://openalex.org/I39555362"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100634965","display_name":"V\u00edctor S\u00e1nchez","orcid":"https://orcid.org/0000-0002-7089-7031"},"institutions":[{"id":"https://openalex.org/I39555362","display_name":"University of Warwick","ror":"https://ror.org/01a77tt86","country_code":"GB","type":"education","lineage":["https://openalex.org/I39555362"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Victor Sanchez","raw_affiliation_strings":["The Univ. of Warwick (United Kingdom)","The University of Warwick, United Kingdom"],"affiliations":[{"raw_affiliation_string":"The Univ. of Warwick (United Kingdom)","institution_ids":["https://openalex.org/I39555362"]},{"raw_affiliation_string":"The University of Warwick, United Kingdom","institution_ids":["https://openalex.org/I39555362"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110483052","display_name":"Hesham EIDaly","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156194","display_name":"Addenbrooke's Hospital","ror":"https://ror.org/055vbxf86","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I2802466933","https://openalex.org/I4210156194"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hesham EIDaly","raw_affiliation_strings":["Addenbrooke's Hospital (United Kingdom)"],"affiliations":[{"raw_affiliation_string":"Addenbrooke's Hospital (United Kingdom)","institution_ids":["https://openalex.org/I4210156194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069179055","display_name":"Nasir Rajpoot","orcid":"https://orcid.org/0000-0002-4706-1308"},"institutions":[{"id":"https://openalex.org/I39555362","display_name":"University of Warwick","ror":"https://ror.org/01a77tt86","country_code":"GB","type":"education","lineage":["https://openalex.org/I39555362"]},{"id":"https://openalex.org/I60342839","display_name":"Qatar University","ror":"https://ror.org/00yhnba62","country_code":"QA","type":"education","lineage":["https://openalex.org/I60342839"]}],"countries":["GB","QA"],"is_corresponding":false,"raw_author_name":"Nasir M. Rajpoot","raw_affiliation_strings":["Qatar Univ.  (Qatar)","The Univ. of Warwick (United Kingdom)"],"affiliations":[{"raw_affiliation_string":"Qatar Univ.  (Qatar)","institution_ids":["https://openalex.org/I60342839"]},{"raw_affiliation_string":"The Univ. of Warwick (United Kingdom)","institution_ids":["https://openalex.org/I39555362"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5036968205"],"corresponding_institution_ids":["https://openalex.org/I39555362"],"apc_list":null,"apc_paid":null,"fwci":0.1841,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57501549,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"9420","issue":null,"first_page":"94200T","last_page":"94200T"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9966999888420105,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9966999888420105,"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/T11628","display_name":"Myeloproliferative Neoplasms: Diagnosis and Treatment","score":0.9735999703407288,"subfield":{"id":"https://openalex.org/subfields/2716","display_name":"Genetics"},"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/T11330","display_name":"Systemic Sclerosis and Related Diseases","score":0.9703999757766724,"subfield":{"id":"https://openalex.org/subfields/2734","display_name":"Pathology and Forensic Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/active-contour-model","display_name":"Active contour model","score":0.6891663074493408},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6462744474411011},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6038699746131897},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5873914957046509},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5552882552146912},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5502023696899414},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5202094912528992},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.45865556597709656},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.45403361320495605},{"id":"https://openalex.org/keywords/trephine","display_name":"Trephine","score":0.4234587252140045},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3651062250137329},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3644068241119385},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.16410475969314575},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1476687788963318},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.11304649710655212}],"concepts":[{"id":"https://openalex.org/C112353826","wikidata":"https://www.wikidata.org/wiki/Q127313","display_name":"Active contour model","level":4,"score":0.6891663074493408},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6462744474411011},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6038699746131897},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5873914957046509},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5552882552146912},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5502023696899414},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5202094912528992},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.45865556597709656},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.45403361320495605},{"id":"https://openalex.org/C2776232749","wikidata":"https://www.wikidata.org/wiki/Q1796877","display_name":"Trephine","level":2,"score":0.4234587252140045},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3651062250137329},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3644068241119385},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16410475969314575},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1476687788963318},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.11304649710655212}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2082064","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2082064","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1597336200","https://openalex.org/W1971251948","https://openalex.org/W1990701931","https://openalex.org/W2008970948","https://openalex.org/W2051765910","https://openalex.org/W2057114171","https://openalex.org/W2059164206","https://openalex.org/W2097533751","https://openalex.org/W2116040950","https://openalex.org/W4237391193","https://openalex.org/W6635816984","https://openalex.org/W6665423862","https://openalex.org/W6674569091"],"related_works":["https://openalex.org/W2004162203","https://openalex.org/W2034210553","https://openalex.org/W82527077","https://openalex.org/W1967564617","https://openalex.org/W2407791760","https://openalex.org/W2441111041","https://openalex.org/W2428140635","https://openalex.org/W3204042767","https://openalex.org/W2320349947","https://openalex.org/W2076525454"],"abstract_inverted_index":{"The":[0,139],"assessment":[1],"of":[2,17,20,33,56,93,117,135,159,182,208,227,235],"megakaryocytes":[3],"(MKs)":[4],"in":[5,14,51,100],"bone":[6,26],"marrow":[7,27],"trephine":[8,28],"images":[9,29],"is":[10,124,192],"an":[11,60,106,180,206,245],"important":[12],"step":[13],"the":[15,52,85,111,127,133,157,165,171,195,198,215,225,233],"classification":[16],"different":[18],"subtypes":[19],"myeloproliferative":[21],"neoplasms":[22],"(MPNs).":[23],"In":[24,46],"general,":[25],"include":[30],"several":[31],"types":[32],"cells":[34],"mixed":[35],"together,":[36],"which":[37],"make":[38],"it":[39],"quite":[40],"difficult":[41],"to":[42,48,76,82,109,130,220],"visually":[43],"identify":[44,77],"MKs.":[45,119],"order":[47],"aid":[49],"hematopathologists":[50],"identification":[53],"and":[54,69,80,88,95,105,137,200,241],"study":[55],"MKs,":[57,197],"we":[58],"develop":[59],"image":[61],"processing":[62],"framework":[63],"with":[64,113,179,205],"supervised":[65],"machine":[66,172],"learning":[67,173],"approaches":[68],"a":[70,91,101,114],"novel":[71],"circumscribing":[72,141,188],"active":[73,122,142,189,223],"contour":[74,123,143,190],"model":[75,144,191],"potential":[78,177],"MKs":[79,129,161,178,237],"then":[81],"accurately":[83,131],"delineate":[84,132],"corresponding":[86],"nucleus":[87,136,199],"membrane.":[89,138],"Specifically,":[90],"number":[92],"color":[94],"texture":[96],"features":[97],"are":[98,203],"used":[99,125],"nave":[102],"Bayesian":[103],"classifier":[104,108],"Adaboost":[107],"locate":[110],"regions":[112],"high":[115],"probability":[116,234],"depicting":[118,160,236],"A":[120],"region-based":[121,222],"on":[126,151,156,194,232],"candidate":[128,196],"boundaries":[134,202],"proposed":[140],"employs":[145],"external":[146,229],"forces":[147,230],"not":[148],"only":[149],"based":[150,231],"pixel":[152],"intensities,":[153],"but":[154],"also":[155],"probabilities":[158],"as":[162,212],"computed":[163],"by":[164,214,244],"classifiers.":[166],"Experimental":[167],"results":[168],"suggest":[169],"that":[170],"approach":[174],"can":[175],"detect":[176],"accuracy":[181,207],"more":[183,209],"than":[184,210],"75%.":[185],"When":[186],"our":[187],"employed":[193],"membrane":[201],"segmented":[204],"80%":[211],"measured":[213],"Dice":[216],"similarity":[217],"coefficient.":[218],"Compared":[219],"traditional":[221],"contours,":[224],"use":[226],"additional":[228],"improves":[238],"segmentation":[239],"performance":[240],"computational":[242],"time":[243],"average":[246],"5%.":[247]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}