{"id":"https://openalex.org/W2962998951","doi":"https://doi.org/10.1109/ijcnn.2016.7727867","title":"Radon features and barcodes for medical image retrieval via SVM","display_name":"Radon features and barcodes for medical image retrieval via SVM","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2962998951","doi":"https://doi.org/10.1109/ijcnn.2016.7727867","mag":"2962998951"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727867","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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/A5101667971","display_name":"Shujin Zhu","orcid":"https://orcid.org/0000-0001-6859-1618"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shujin Zhu","raw_affiliation_strings":["School of Electronic & Optical Engineering, Nanjing University of Science & Technology, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic & Optical Engineering, Nanjing University of Science & Technology, Jiangsu, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038566332","display_name":"Hamid R. Tizhoosh","orcid":"https://orcid.org/0000-0001-5488-601X"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"H.R. Tizhoosh","raw_affiliation_strings":["KIMIA Lab, University of Waterloo, Canada"],"affiliations":[{"raw_affiliation_string":"KIMIA Lab, University of Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101667971"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":1.169,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.86092604,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"5065","last_page":"5071"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9998000264167786,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9988999962806702,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9962000250816345,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.8278242349624634},{"id":"https://openalex.org/keywords/barcode","display_name":"Barcode","score":0.7952096462249756},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7319610118865967},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.6881545782089233},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6501770615577698},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6256536245346069},{"id":"https://openalex.org/keywords/content-based-image-retrieval","display_name":"Content-based image retrieval","score":0.6016458868980408},{"id":"https://openalex.org/keywords/radon","display_name":"Radon","score":0.58695387840271},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.523287832736969},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4593397378921509},{"id":"https://openalex.org/keywords/hamming-distance","display_name":"Hamming distance","score":0.4317554533481598},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41899824142456055},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41291943192481995},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.06627574563026428}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8278242349624634},{"id":"https://openalex.org/C2776841711","wikidata":"https://www.wikidata.org/wiki/Q856","display_name":"Barcode","level":2,"score":0.7952096462249756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7319610118865967},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.6881545782089233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6501770615577698},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6256536245346069},{"id":"https://openalex.org/C2780052074","wikidata":"https://www.wikidata.org/wiki/Q1128648","display_name":"Content-based image retrieval","level":4,"score":0.6016458868980408},{"id":"https://openalex.org/C545943180","wikidata":"https://www.wikidata.org/wiki/Q1133","display_name":"Radon","level":2,"score":0.58695387840271},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.523287832736969},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4593397378921509},{"id":"https://openalex.org/C193319292","wikidata":"https://www.wikidata.org/wiki/Q272172","display_name":"Hamming distance","level":2,"score":0.4317554533481598},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41899824142456055},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41291943192481995},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.06627574563026428},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2016.7727867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727867","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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":33,"referenced_works":["https://openalex.org/W34176136","https://openalex.org/W1428511354","https://openalex.org/W1586847502","https://openalex.org/W1976748469","https://openalex.org/W1994022528","https://openalex.org/W1999093385","https://openalex.org/W2001831401","https://openalex.org/W2020969339","https://openalex.org/W2023234912","https://openalex.org/W2037407504","https://openalex.org/W2086962047","https://openalex.org/W2089441731","https://openalex.org/W2119821739","https://openalex.org/W2122369784","https://openalex.org/W2133533561","https://openalex.org/W2136968720","https://openalex.org/W2149250815","https://openalex.org/W2151619249","https://openalex.org/W2157640836","https://openalex.org/W2166289851","https://openalex.org/W2169177311","https://openalex.org/W2172000360","https://openalex.org/W2172177969","https://openalex.org/W2202393049","https://openalex.org/W2259336176","https://openalex.org/W2268345094","https://openalex.org/W2964155457","https://openalex.org/W3105428393","https://openalex.org/W4239510810","https://openalex.org/W4246414422","https://openalex.org/W6650816768","https://openalex.org/W6684872329","https://openalex.org/W6991965754"],"related_works":["https://openalex.org/W2345184372","https://openalex.org/W3013515612","https://openalex.org/W2136184105","https://openalex.org/W2187500075","https://openalex.org/W2336974148","https://openalex.org/W2340338190","https://openalex.org/W2962998951","https://openalex.org/W2125018361","https://openalex.org/W3005084132","https://openalex.org/W2608994187"],"abstract_inverted_index":{"For":[0],"more":[1],"than":[2],"two":[3],"decades,":[4],"research":[5],"has":[6,156,184],"been":[7],"performed":[8],"on":[9],"content-based":[10,25],"image":[11,27,45,61,81,92,168],"retrieval":[12,28],"(CBIR).":[13],"By":[14],"combining":[15],"Radon":[16,41,55,84,113,127],"projections":[17,42,85],"and":[18,53,86,169,183],"the":[19,39,54,87,90,96,105,112,116,121,132,139,157,164],"support":[20],"vector":[21],"machines":[22],"(SVM),":[23],"a":[24,63,79],"medical":[26],"method":[29,100,134,155],"is":[30,66,82,101,135,180],"presented":[31],"in":[32,62,147],"this":[33],"work.":[34],"The":[35,129,150,177],"proposed":[36,133],"approach":[37,178],"employs":[38],"normalized":[40],"with":[43,107,143],"corresponding":[44],"category":[46],"labels":[47],"to":[48,70,103,159],"build":[49],"an":[50],"SVM":[51,123],"classifier,":[52],"barcode":[56,88,114],"database":[57],"which":[58],"encodes":[59],"every":[60],"binary":[64],"format":[65],"also":[67],"generated":[68],"simultaneously":[69],"tag":[71],"all":[72],"images.":[73],"To":[74],"retrieve":[75,160],"similar":[76,161],"images":[77,106,146],"when":[78],"query":[80,91,167],"given,":[83],"of":[89,111,131],"are":[93],"generated.":[94],"Subsequently,":[95],"k-nearest":[97],"neighbor":[98],"search":[99],"applied":[102],"find":[104],"minimum":[108],"Hamming":[109],"distance":[110],"within":[115],"same":[117],"class":[118],"predicted":[119],"by":[120,137,175],"trained":[122],"classifier":[124],"that":[125,153],"uses":[126],"features.":[128],"performance":[130],"validated":[136],"using":[138],"IRMA":[140],"2009":[141],"dataset":[142],"14,410":[144],"x-ray":[145],"57":[148],"categories.":[149],"results":[151],"demonstrate":[152],"our":[154],"capacity":[158],"responses":[162],"for":[163,171],"correctly":[165],"identified":[166],"even":[170],"those":[172],"mistakenly":[173],"classified":[174],"SVM.":[176],"further":[179],"very":[181],"fast":[182],"low":[185],"memory":[186],"requirement.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}