{"id":"https://openalex.org/W2962202225","doi":"https://doi.org/10.1109/tbme.2019.2928997","title":"Analysis\u2013Synthesis Learning With Shared Features: Algorithms for Histology Image Classification","display_name":"Analysis\u2013Synthesis Learning With Shared Features: Algorithms for Histology Image Classification","publication_year":2019,"publication_date":"2019-07-16","ids":{"openalex":"https://openalex.org/W2962202225","doi":"https://doi.org/10.1109/tbme.2019.2928997","mag":"2962202225","pmid":"https://pubmed.ncbi.nlm.nih.gov/31329103"},"language":"en","primary_location":{"id":"doi:10.1109/tbme.2019.2928997","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbme.2019.2928997","pdf_url":null,"source":{"id":"https://openalex.org/S5240358","display_name":"IEEE Transactions on Biomedical Engineering","issn_l":"0018-9294","issn":["0018-9294","1558-2531"],"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 Biomedical Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5033386657","display_name":"Xuelu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuelu Li","raw_affiliation_strings":["Department of Electrical Engineering, Pennsylvania State University, University Park, USA"],"raw_orcid":"https://orcid.org/0000-0003-0217-9350","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Pennsylvania State University, University Park, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014013504","display_name":"Vishal Monga","orcid":"https://orcid.org/0000-0002-5100-2263"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vishal Monga","raw_affiliation_strings":["Department of Electrical Engineering, Pennsylvania State University"],"raw_orcid":"https://orcid.org/0000-0002-5100-2263","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Pennsylvania State University","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067785367","display_name":"U. K. Arvind Rao","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"U. K. Arvind Rao","raw_affiliation_strings":["Department of Computational Medicine and Bioinformatics and the Department of Radiation Oncology, University of Michigan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computational Medicine and Bioinformatics and the Department of Radiation Oncology, University of Michigan","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9883,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.82088583,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"67","issue":"4","first_page":"1061","last_page":"1073"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9154999852180481,"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"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9154999852180481,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.01590000092983246,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.014399999752640724,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7401859164237976},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6787346601486206},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5533362627029419},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.548843264579773},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5138464570045471},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4548528790473938},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.43940269947052},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42906510829925537},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4242985248565674},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.41508522629737854},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35959118604660034},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.28738099336624146}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7401859164237976},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6787346601486206},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5533362627029419},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.548843264579773},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5138464570045471},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4548528790473938},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.43940269947052},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42906510829925537},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4242985248565674},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.41508522629737854},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35959118604660034},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28738099336624146},{"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":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006652","descriptor_name":"Histological Techniques","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006652","descriptor_name":"Histological Techniques","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006652","descriptor_name":"Histological Techniques","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tbme.2019.2928997","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbme.2019.2928997","pdf_url":null,"source":{"id":"https://openalex.org/S5240358","display_name":"IEEE Transactions on Biomedical Engineering","issn_l":"0018-9294","issn":["0018-9294","1558-2531"],"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 Biomedical Engineering","raw_type":"journal-article"},{"id":"pmid:31329103","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31329103","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on bio-medical engineering","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G4430796477","display_name":null,"funder_award_id":"RSG-16-005-01","funder_id":"https://openalex.org/F4320306095","funder_display_name":"American Cancer Society"},{"id":"https://openalex.org/G6603871621","display_name":null,"funder_award_id":"R01CA21495501A1","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"}],"funders":[{"id":"https://openalex.org/F4320306095","display_name":"American Cancer Society","ror":"https://ror.org/02e463172"},{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W129703402","https://openalex.org/W134688180","https://openalex.org/W1583676656","https://openalex.org/W1680392829","https://openalex.org/W1835905048","https://openalex.org/W1921479191","https://openalex.org/W1972552638","https://openalex.org/W1998929974","https://openalex.org/W2000323691","https://openalex.org/W2037696125","https://openalex.org/W2062118960","https://openalex.org/W2079385922","https://openalex.org/W2083906081","https://openalex.org/W2092853008","https://openalex.org/W2100556411","https://openalex.org/W2103243046","https://openalex.org/W2103972604","https://openalex.org/W2107901014","https://openalex.org/W2127831489","https://openalex.org/W2129812935","https://openalex.org/W2131748184","https://openalex.org/W2139852318","https://openalex.org/W2143093135","https://openalex.org/W2150912629","https://openalex.org/W2153635508","https://openalex.org/W2159551006","https://openalex.org/W2159931675","https://openalex.org/W2163605009","https://openalex.org/W2165879419","https://openalex.org/W2166371785","https://openalex.org/W2496047471","https://openalex.org/W2554892747","https://openalex.org/W2592929672","https://openalex.org/W2609584387","https://openalex.org/W2618530766","https://openalex.org/W2620578070","https://openalex.org/W2637598222","https://openalex.org/W2766400329","https://openalex.org/W2766865858","https://openalex.org/W2964181843","https://openalex.org/W3100455090","https://openalex.org/W6634837548","https://openalex.org/W6650392997","https://openalex.org/W6679331151","https://openalex.org/W6680925037","https://openalex.org/W6684213969"],"related_works":["https://openalex.org/W2922314686","https://openalex.org/W2982642565","https://openalex.org/W2113421559","https://openalex.org/W3164111940","https://openalex.org/W2005234362","https://openalex.org/W2162970382","https://openalex.org/W1997235926","https://openalex.org/W4309346246","https://openalex.org/W2565656575","https://openalex.org/W3162639707"],"abstract_inverted_index":{"OBJECTIVE:":[0],"The":[1,191],"diversity":[2],"of":[3,44,68,147,176,228],"tissue":[4,203,213],"structure":[5],"in":[6,49,133,165,247],"histopathological":[7,166],"images":[8,73,98,167],"makes":[9],"feature":[10,33,120],"extraction":[11],"for":[12,32,95],"classification":[13,23,246],"a":[14,20,57,65,85,105,148,153,179,187],"challenging":[15,197],"task.":[16],"Dictionary":[17],"learning":[18,89,110,146],"within":[19],"sparse":[21],"representation-based":[22],"(SRC)":[24],"framework":[25],"has":[26],"been":[27],"shown":[28],"to":[29,78,114,138,243],"be":[30,47],"successful":[31],"discovery.":[34],"However,":[35],"there":[36],"exist":[37],"stiff":[38],"practical":[39],"challenges:":[40],"1)":[41,201],"computational":[42],"complexity":[43,224],"SRC":[45],"can":[46],"onerous":[48],"the":[50,103,116,119,123,134,145,229],"decision":[51],"stage":[52],"since":[53],"it":[54],"involves":[55],"solving":[56],"sparsity":[58,180],"constrained":[59],"optimization":[60,130],"problem":[61],"and":[62,71,108,118,152,163,198,209,225],"often":[63],"over":[64,231],"large":[66],"number":[67],"image":[69],"patches;":[70],"2)":[72,205],"from":[74,168],"distinct":[75,169],"classes":[76],"continue":[77],"share":[79],"several":[80],"geometric":[81],"features.":[82],"We":[83,171],"propose":[84],"novel":[86],"analysis-synthesis":[87],"model":[88,111],"with":[90,178,238],"shared":[91,150,154,236],"features":[92,237],"algorithm":[93],"(ALSF)":[94],"classifying":[96],"such":[97],"more":[99,158],"effectively.":[100],"METHODS:":[101],"In":[102],"ALSF,":[104],"joint":[106],"analysis":[107,155],"synthesis":[109],"is":[112,131,193],"introduced":[113],"learn":[115],"classifier":[117],"extractor":[121],"at":[122],"same":[124],"time.":[125],"Unlike":[126],"SRC,":[127],"no":[128],"explicit":[129],"needed":[132],"inference":[135],"phase":[136],"leading":[137],"much":[139],"reduced":[140],"computation.":[141],"Crucially,":[142],"we":[143],"introduce":[144],"low-rank":[149],"dictionary":[151],"operator,":[156],"which":[157],"accurately":[159],"represents":[160],"both":[161,223],"similarities":[162],"differences":[164],"classes.":[170],"also":[172],"develop":[173],"an":[174],"extension":[175],"ALSF":[177,192,230],"constraint,":[181],"whose":[182],"presence":[183],"or":[184],"absence":[185],"facilitates":[186],"cost-performance":[188],"tradeoff.":[189],"RESULTS:":[190],"evaluated":[194],"on":[195],"three":[196],"well-known":[199],"datasets:":[200],"spleen":[202],"images;":[204,208],"brain":[206],"tumor":[207],"3)":[210],"breast":[211],"cancer":[212],"dataset,":[214],"provided":[215],"by":[216],"different":[217],"organizations.":[218],"CONCLUSION:":[219],"Experimental":[220],"results":[221],"demonstrate":[222],"performance":[226],"benefits":[227],"state-of-the-art":[232],"alternatives.":[233],"SIGNIFICANCE:":[234],"Modeling":[235],"appropriate":[239],"quantitative":[240],"constraints":[241],"lead":[242],"significantly":[244],"improved":[245],"histopathology.":[248]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
