{"id":"https://openalex.org/W2085569734","doi":"https://doi.org/10.1109/icnc.2013.6818206","title":"Spectral feature extraction of blood cells based on hyperspectral data","display_name":"Spectral feature extraction of blood cells based on hyperspectral data","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2085569734","doi":"https://doi.org/10.1109/icnc.2013.6818206","mag":"2085569734"},"language":"en","primary_location":{"id":"doi:10.1109/icnc.2013.6818206","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2013.6818206","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 Ninth International Conference on Natural Computation (ICNC)","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/A5100853697","display_name":"Chunni Dai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210154361","display_name":"Shanghai Jian Qiao University","ror":"https://ror.org/04xdqtw10","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210154361"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunni Dai","raw_affiliation_strings":["School of Information Technology, Shanghai Jianqiao College, Shanghai, PR China","School of Information Technology, Shanghai Jianqiao College, Shanghai 200139, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology, Shanghai Jianqiao College, Shanghai, PR China","institution_ids":["https://openalex.org/I4210154361"]},{"raw_affiliation_string":"School of Information Technology, Shanghai Jianqiao College, Shanghai 200139, PR China","institution_ids":["https://openalex.org/I4210154361"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054129534","display_name":"Jingao Liu","orcid":"https://orcid.org/0000-0002-8800-5898"},"institutions":[{"id":"https://openalex.org/I4210154361","display_name":"Shanghai Jian Qiao University","ror":"https://ror.org/04xdqtw10","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210154361"]},{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingao Liu","raw_affiliation_strings":["School of Information Science & Technology, East China Normal University, Shanghai, PR China","School of Information Technology, Shanghai Jianqiao College, Shanghai 200139, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science & Technology, East China Normal University, Shanghai, PR China","institution_ids":["https://openalex.org/I66867065"]},{"raw_affiliation_string":"School of Information Technology, Shanghai Jianqiao College, Shanghai 200139, PR China","institution_ids":["https://openalex.org/I4210154361"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2763,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.62398258,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"3","issue":null,"first_page":"1439","last_page":"1443"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9987000226974487,"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":0.9987000226974487,"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/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.988099992275238,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9125938415527344},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7183414697647095},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6286020278930664},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6222546696662903},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.616194486618042},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.535089910030365},{"id":"https://openalex.org/keywords/spectral-imaging","display_name":"Spectral imaging","score":0.5027561187744141},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.47463545203208923},{"id":"https://openalex.org/keywords/spectral-analysis","display_name":"Spectral analysis","score":0.4498915374279022},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.4390799403190613},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41870155930519104},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.41123324632644653},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40670686960220337},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.28512755036354065},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.17357492446899414},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1650407910346985},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13879945874214172},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.13161194324493408},{"id":"https://openalex.org/keywords/spectroscopy","display_name":"Spectroscopy","score":0.11288502812385559}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9125938415527344},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7183414697647095},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6286020278930664},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6222546696662903},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.616194486618042},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.535089910030365},{"id":"https://openalex.org/C3232514","wikidata":"https://www.wikidata.org/wiki/Q7575196","display_name":"Spectral imaging","level":2,"score":0.5027561187744141},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.47463545203208923},{"id":"https://openalex.org/C2983668108","wikidata":"https://www.wikidata.org/wiki/Q280453","display_name":"Spectral analysis","level":3,"score":0.4498915374279022},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.4390799403190613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41870155930519104},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.41123324632644653},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40670686960220337},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.28512755036354065},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.17357492446899414},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1650407910346985},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13879945874214172},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13161194324493408},{"id":"https://openalex.org/C32891209","wikidata":"https://www.wikidata.org/wiki/Q483666","display_name":"Spectroscopy","level":2,"score":0.11288502812385559},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnc.2013.6818206","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2013.6818206","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 Ninth International Conference on Natural Computation (ICNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.7699999809265137,"display_name":"Good health and well-being"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W155685019","https://openalex.org/W1605337581","https://openalex.org/W1967287598","https://openalex.org/W1973904960","https://openalex.org/W2006536226","https://openalex.org/W2014467703","https://openalex.org/W2022520652","https://openalex.org/W2047851356","https://openalex.org/W2093525669","https://openalex.org/W2097863358","https://openalex.org/W2108080209","https://openalex.org/W2117333179","https://openalex.org/W2119107075","https://openalex.org/W2151543996","https://openalex.org/W2151632851","https://openalex.org/W2156220041","https://openalex.org/W2164396308","https://openalex.org/W2304117705","https://openalex.org/W6606231175","https://openalex.org/W6662329799"],"related_works":["https://openalex.org/W2911259277","https://openalex.org/W4386427838","https://openalex.org/W3047444742","https://openalex.org/W2391021239","https://openalex.org/W2049189005","https://openalex.org/W2054836752","https://openalex.org/W3178760882","https://openalex.org/W2765547586","https://openalex.org/W2107175121","https://openalex.org/W2352868551"],"abstract_inverted_index":{"The":[0,69],"aim":[1],"of":[2,13,16,29,52,78,120],"this":[3,74],"paper":[4,75],"is":[5,60],"to":[6,9,96,123],"investigate":[7],"how":[8],"extract":[10],"spectral":[11,63,70,83,87,102],"features":[12,111],"five":[14],"kinds":[15],"blood":[17,30,127],"cells":[18,31,128],"before":[19],"they":[20],"are":[21,32,45,95],"classified":[22],"and":[23,37,66,107,125],"counted.":[24],"Here":[25],"the":[26,50],"hyperspectral":[27,57],"images":[28],"taken":[33],"from":[34,41,62],"leukemic":[35],"patients":[36],"healthy":[38],"persons.":[39],"Different":[40],"traditional":[42],"methods":[43],"which":[44,117],"usually":[46],"based":[47,55],"on":[48,56],"morphology,":[49],"method":[51],"feature":[53],"extraction":[54],"imaging":[58],"technique":[59],"mainly":[61],"pattern":[64,71],"traits":[65,72],"similarity":[67],"measures.":[68],"in":[73,82,129],"includes":[76],"characteristics":[77],"troughs":[79],"or":[80],"crests":[81],"patterns":[84],"such":[85],"as":[86],"absorption":[88],"index,":[89],"location,":[90],"intensity,":[91],"symmetry.":[92],"Similarity":[93],"measures":[94],"measure":[97],"two":[98],"pattern's":[99],"relationship":[100],"using":[101],"angle":[103],"mapping,":[104],"correlation":[105],"coefficient":[106],"covariance.":[108],"Altogether":[109],"these":[110],"contain":[112],"more":[113],"than":[114],"thirty":[115],"characteristics,":[116],"would":[118],"be":[119],"great":[121],"use":[122],"segment":[124],"classify":[126],"later":[130],"work.":[131]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
