{"id":"https://openalex.org/W2014323679","doi":"https://doi.org/10.4018/jmdem.2011040104","title":"Multimodal Information Integration and Fusion for Histology Image Classification","display_name":"Multimodal Information Integration and Fusion for Histology Image Classification","publication_year":2011,"publication_date":"2011-04-01","ids":{"openalex":"https://openalex.org/W2014323679","doi":"https://doi.org/10.4018/jmdem.2011040104","mag":"2014323679"},"language":"en","primary_location":{"id":"doi:10.4018/jmdem.2011040104","is_oa":false,"landing_page_url":"https://doi.org/10.4018/jmdem.2011040104","pdf_url":null,"source":{"id":"https://openalex.org/S87630009","display_name":"International Journal of Multimedia Data Engineering and Management","issn_l":"1947-8534","issn":["1947-8534","1947-8542"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Multimedia Data Engineering and Management","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/A5087537584","display_name":"Tao Meng","orcid":"https://orcid.org/0000-0002-9669-3387"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tao Meng","raw_affiliation_strings":["University of Miami, USA","(University of Miami, USA)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Miami, USA","institution_ids":["https://openalex.org/I145608581"]},{"raw_affiliation_string":"(University of Miami, USA)","institution_ids":["https://openalex.org/I145608581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036221136","display_name":"Mei\u2010Ling Shyu","orcid":"https://orcid.org/0000-0003-0902-0844"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mei-Ling Shyu","raw_affiliation_strings":["University of Miami, USA","(University of Miami, USA)"],"raw_orcid":"https://orcid.org/0000-0003-0902-0844","affiliations":[{"raw_affiliation_string":"University of Miami, USA","institution_ids":["https://openalex.org/I145608581"]},{"raw_affiliation_string":"(University of Miami, USA)","institution_ids":["https://openalex.org/I145608581"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100342078","display_name":"Lin Lin","orcid":"https://orcid.org/0000-0003-3397-6002"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lin Lin","raw_affiliation_strings":["University of Miami, USA","(University of Miami, USA)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Miami, USA","institution_ids":["https://openalex.org/I145608581"]},{"raw_affiliation_string":"(University of Miami, USA)","institution_ids":["https://openalex.org/I145608581"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I145608581"],"apc_list":null,"apc_paid":null,"fwci":1.0299,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.79116955,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"2","issue":"2","first_page":"54","last_page":"70"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9980000257492065,"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":0.9980000257492065,"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/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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9968000054359436,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7979602217674255},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5674041509628296},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5593793392181396},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5539396405220032},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5223506689071655},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5036570429801941},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4585329294204712},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.42493438720703125},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4109758138656616},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3935914635658264},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3470922112464905}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7979602217674255},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5674041509628296},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5593793392181396},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5539396405220032},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5223506689071655},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5036570429801941},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4585329294204712},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.42493438720703125},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4109758138656616},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3935914635658264},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3470922112464905},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4018/jmdem.2011040104","is_oa":false,"landing_page_url":"https://doi.org/10.4018/jmdem.2011040104","pdf_url":null,"source":{"id":"https://openalex.org/S87630009","display_name":"International Journal of Multimedia Data Engineering and Management","issn_l":"1947-8534","issn":["1947-8534","1947-8542"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Multimedia Data Engineering and Management","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:igg:jmdem0:v:2:y:2011:i:2:p:54-70","is_oa":false,"landing_page_url":"http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jmdem.2011040104","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W134688180","https://openalex.org/W209809163","https://openalex.org/W1553703108","https://openalex.org/W1570448133","https://openalex.org/W1968969471","https://openalex.org/W1971993587","https://openalex.org/W1997944424","https://openalex.org/W2011646445","https://openalex.org/W2027925344","https://openalex.org/W2030041075","https://openalex.org/W2032673367","https://openalex.org/W2034931370","https://openalex.org/W2052828499","https://openalex.org/W2058560943","https://openalex.org/W2072422078","https://openalex.org/W2076934502","https://openalex.org/W2087030102","https://openalex.org/W2102695035","https://openalex.org/W2107554012","https://openalex.org/W2111254256","https://openalex.org/W2129540691","https://openalex.org/W2130263725","https://openalex.org/W2146071495","https://openalex.org/W2148661353","https://openalex.org/W2150575849","https://openalex.org/W2151340211","https://openalex.org/W2154917588","https://openalex.org/W2161296869","https://openalex.org/W2165879419","https://openalex.org/W2275185217","https://openalex.org/W2915771011","https://openalex.org/W2966207845"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W1980381208","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W4230315250","https://openalex.org/W3114272811"],"abstract_inverted_index":{"Biomedical":[0],"imaging":[1,18],"technology":[2],"has":[3,59],"become":[4],"an":[5],"important":[6,51],"tool":[7],"for":[8,41,95,142],"medical":[9],"research":[10],"and":[11,22,27,58,65,87,177],"clinical":[12],"practice.":[13],"A":[14],"large":[15],"amount":[16],"of":[17,36,49,74,90,100],"data":[19,30,162,166],"is":[20,47,93,108,114,134],"generated":[21],"collected":[23],"every":[24],"day.":[25],"Managing":[26],"analyzing":[28],"these":[29],"sets":[31],"require":[32],"the":[33,37,50,54,120,127,138,150,160,185],"corresponding":[34],"development":[35],"computer":[38],"based":[39,115],"algorithms":[40],"automatic":[42],"processing.":[43],"Histology":[44],"image":[45,76],"classification":[46,140],"one":[48,117],"tasks":[52],"in":[53,62,123,184],"bio-image":[55],"informatics":[56],"field":[57],"broad":[60],"applications":[61],"phenotype":[63],"description":[64],"disease":[66],"diagnosis.":[67],"This":[68],"study":[69],"proposes":[70],"a":[71,88],"novel":[72],"framework":[73,173],"histology":[75],"classification.":[77],"The":[78,168],"original":[79,124],"images":[80],"are":[81],"first":[82],"divided":[83],"into":[84],"several":[85,156],"blocks":[86],"set":[89],"visual":[91],"features":[92],"extracted":[94],"each":[96,112,143],"block.":[97],"An":[98],"array":[99],"C-RSPM":[101],"(Collateral":[102],"Representative":[103],"Subspace":[104],"Projection":[105],"Modeling)":[106],"models":[107],"then":[109],"built":[110],"that":[111,171],"model":[113],"on":[116],"block":[118],"from":[119,164],"same":[121],"location":[122],"images.":[125],"Finally,":[126],"C-Value":[128],"Enhanced":[129],"Majority":[130],"Voting":[131],"(CEWMV)":[132],"algorithm":[133],"developed":[135],"to":[136],"derive":[137],"final":[139],"label":[141],"testing":[144],"image.":[145],"To":[146],"evaluate":[147],"this":[148,172],"framework,":[149],"authors":[151],"compare":[152],"its":[153],"performance":[154,176],"with":[155],"well-known":[157],"classifiers":[158,183],"using":[159],"benchmark":[161],"available":[163],"IICBU":[165],"repository.":[167],"results":[169],"demonstrate":[170],"achieves":[174],"promising":[175],"performs":[178],"significantly":[179],"better":[180],"than":[181],"other":[182],"comparison.":[186]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-11T06:19:23.411458","created_date":"2025-10-10T00:00:00"}