{"id":"https://openalex.org/W2150378175","doi":"https://doi.org/10.1109/icip.2009.5414558","title":"Channelized hotelling observers for the detection of 2D signals in 3D simulated images","display_name":"Channelized hotelling observers for the detection of 2D signals in 3D simulated images","publication_year":2009,"publication_date":"2009-11-01","ids":{"openalex":"https://openalex.org/W2150378175","doi":"https://doi.org/10.1109/icip.2009.5414558","mag":"2150378175"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2009.5414558","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2009.5414558","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 16th IEEE International Conference on Image Processing (ICIP)","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/A5073297953","display_name":"Ljiljana Plati\u0161a","orcid":"https://orcid.org/0000-0001-6228-0587"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Ljiljana Platisa","raw_affiliation_strings":["TELIN-IPI-IBBT, Ghent University (Ghent), Ghent, Belgium"],"affiliations":[{"raw_affiliation_string":"TELIN-IPI-IBBT, Ghent University (Ghent), Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101986863","display_name":"Bart Goossens","orcid":"https://orcid.org/0000-0002-4942-132X"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Bart Goossens","raw_affiliation_strings":["TELIN-IPI-IBBT, Ghent University (Ghent), Ghent, Belgium"],"affiliations":[{"raw_affiliation_string":"TELIN-IPI-IBBT, Ghent University (Ghent), Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067368696","display_name":"Ewout Vansteenkiste","orcid":null},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Ewout Vansteenkiste","raw_affiliation_strings":["TELIN-IPI-IBBT, Ghent University (Ghent), Ghent, Belgium"],"affiliations":[{"raw_affiliation_string":"TELIN-IPI-IBBT, Ghent University (Ghent), Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034816801","display_name":"Aldo Badano","orcid":"https://orcid.org/0000-0003-3712-6670"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aldo Badano","raw_affiliation_strings":["FDA Silver Spring MD, CDRH, USA"],"affiliations":[{"raw_affiliation_string":"FDA Silver Spring MD, CDRH, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071483672","display_name":"Wilfried Philips","orcid":"https://orcid.org/0000-0003-4456-4353"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Wilfried Philips","raw_affiliation_strings":["TELIN-IPI-IBBT, Ghent University (Ghent), Ghent, Belgium"],"affiliations":[{"raw_affiliation_string":"TELIN-IPI-IBBT, Ghent University (Ghent), Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5073297953"],"corresponding_institution_ids":["https://openalex.org/I32597200"],"apc_list":null,"apc_paid":null,"fwci":0.9873,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78311791,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"4","issue":null,"first_page":"1781","last_page":"1784"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9984999895095825,"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":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/channelized","display_name":"Channelized","score":0.8889995217323303},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.708471417427063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5980132818222046},{"id":"https://openalex.org/keywords/observer","display_name":"Observer (physics)","score":0.5541490912437439},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5120123028755188},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5042625665664673},{"id":"https://openalex.org/keywords/wafer","display_name":"Wafer","score":0.4605826735496521},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4470686912536621},{"id":"https://openalex.org/keywords/scalar","display_name":"Scalar (mathematics)","score":0.4398305416107178},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4298701286315918},{"id":"https://openalex.org/keywords/planar","display_name":"Planar","score":0.4221307635307312},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18709716200828552},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.12021207809448242},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10243621468544006}],"concepts":[{"id":"https://openalex.org/C51889082","wikidata":"https://www.wikidata.org/wiki/Q5072521","display_name":"Channelized","level":2,"score":0.8889995217323303},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.708471417427063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5980132818222046},{"id":"https://openalex.org/C2780704645","wikidata":"https://www.wikidata.org/wiki/Q9251458","display_name":"Observer (physics)","level":2,"score":0.5541490912437439},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5120123028755188},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5042625665664673},{"id":"https://openalex.org/C160671074","wikidata":"https://www.wikidata.org/wiki/Q267131","display_name":"Wafer","level":2,"score":0.4605826735496521},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4470686912536621},{"id":"https://openalex.org/C57691317","wikidata":"https://www.wikidata.org/wiki/Q1289248","display_name":"Scalar (mathematics)","level":2,"score":0.4398305416107178},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4298701286315918},{"id":"https://openalex.org/C134786449","wikidata":"https://www.wikidata.org/wiki/Q3391255","display_name":"Planar","level":2,"score":0.4221307635307312},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18709716200828552},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.12021207809448242},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10243621468544006},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip.2009.5414558","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2009.5414558","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 16th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:archive.ugent.be:828904","is_oa":false,"landing_page_url":"http://hdl.handle.net/1854/LU-828904","pdf_url":null,"source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISBN: 9781424456543","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322274","display_name":"iMinds","ror":"https://ror.org/03baec336"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2011531785","https://openalex.org/W2027350525","https://openalex.org/W2043003074","https://openalex.org/W2067543687","https://openalex.org/W2081135434","https://openalex.org/W2099631097","https://openalex.org/W2100328168","https://openalex.org/W2146428417","https://openalex.org/W2161366386","https://openalex.org/W2172890700","https://openalex.org/W4250380670","https://openalex.org/W6685213984"],"related_works":["https://openalex.org/W2358732122","https://openalex.org/W2365358419","https://openalex.org/W2978079700","https://openalex.org/W2373037463","https://openalex.org/W2998321762","https://openalex.org/W2142438192","https://openalex.org/W2159703435","https://openalex.org/W2066521475","https://openalex.org/W2131470200","https://openalex.org/W2068668125"],"abstract_inverted_index":{"Current":[0],"clinical":[1],"practice":[2],"is":[3,26,88,106,120],"increasingly":[4],"moving":[5],"in":[6,34,99],"the":[7,28,59,86,100,104,110,115,126,129,135,139,144,148],"direction":[8],"of":[9,30,44,58,78,94,114,128],"volumetric":[10],"imaging.":[11],"However,":[12],"model":[13,47,56,119,146],"observers":[14],"for":[15,96],"3D":[16],"images":[17],"have":[18],"been":[19],"little":[20],"explored":[21],"so":[22],"far.":[23],"This":[24],"study":[25],"investigating":[27],"task":[29],"detecting":[31],"2D":[32,80,122],"signals":[33],"multi-slice":[35,46,65,71,136],"simulated":[36],"image":[37],"data.":[38],"We":[39],"propose":[40],"a":[41,45,76,79,92,121],"novel":[42],"design":[43],"observer.":[48],"To":[49],"evaluate":[50],"it,":[51],"we":[52],"compare":[53],"three":[54],"different":[55],"designs":[57],"channelized":[60],"Hotelling":[61],"observer":[62],"(CHO),":[63],"two":[64],"and":[66,82,103,142],"one":[67],"single-slice":[68,118,140],"model.":[69,116],"The":[70,117],"models":[72,137],"are":[73],"built":[74],"as":[75],"sequence":[77],"CHO":[81,87,123],"1D":[83],"HO,":[84],"where":[85],"used":[89,107],"to":[90,108],"calculate":[91,109],"vector":[93],"metrics":[95],"each":[97],"slice":[98],"planar":[101],"view":[102],"HO":[105],"final":[111],"scalar":[112],"statistic":[113],"applied":[124],"on":[125],"location":[127],"lesion.":[130],"Our":[131],"results":[132],"show":[133],"that":[134],"outperform":[138],"one,":[141],"here":[143],"new":[145],"surpasses":[147],"existing":[149],"one.":[150]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
