{"id":"https://openalex.org/W3012015674","doi":"https://doi.org/10.1117/12.2549042","title":"Observer-driven texture analysis in CT imaging","display_name":"Observer-driven texture analysis in CT imaging","publication_year":2020,"publication_date":"2020-03-16","ids":{"openalex":"https://openalex.org/W3012015674","doi":"https://doi.org/10.1117/12.2549042","mag":"3012015674"},"language":"en","primary_location":{"id":"doi:10.1117/12.2549042","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2549042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment","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/A5069192131","display_name":"Matthew A. Kupinski","orcid":"https://orcid.org/0009-0004-7386-0500"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew A. Kupinski","raw_affiliation_strings":["Univ. of Arizona (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Arizona (United States)","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017433837","display_name":"Zachary Garrett","orcid":"https://orcid.org/0000-0001-8158-3997"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zachary Garrett","raw_affiliation_strings":["Univ. of Arizona (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Arizona (United States)","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051956554","display_name":"Jiahua Fan","orcid":"https://orcid.org/0000-0002-1629-3034"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiahua Fan","raw_affiliation_strings":["GE Healthcare (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"GE Healthcare (United States)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02548844,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"34","last_page":"34"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9965000152587891,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9955999851226807,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7725014686584473},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7604411840438843},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7532796859741211},{"id":"https://openalex.org/keywords/observer","display_name":"Observer (physics)","score":0.6662478446960449},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5931398868560791},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5536577701568604},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.4990360736846924},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.4974377453327179},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.49141204357147217},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.45677465200424194},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44350650906562805},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4337655007839203},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09066668152809143}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7725014686584473},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7604411840438843},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7532796859741211},{"id":"https://openalex.org/C2780704645","wikidata":"https://www.wikidata.org/wiki/Q9251458","display_name":"Observer (physics)","level":2,"score":0.6662478446960449},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5931398868560791},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5536577701568604},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.4990360736846924},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.4974377453327179},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.49141204357147217},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.45677465200424194},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44350650906562805},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4337655007839203},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09066668152809143},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1117/12.2549042","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2549042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.arizona.edu:10150/650740","is_oa":false,"landing_page_url":"http://hdl.handle.net/10150/650740","pdf_url":null,"source":{"id":"https://openalex.org/S4306400271","display_name":"UA Campus Repository (The University of Arizona)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138006243","host_organization_name":"University of Arizona","host_organization_lineage":["https://openalex.org/I138006243"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment","raw_type":"Proceedings"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2009600292","https://openalex.org/W2044881980","https://openalex.org/W2071987554"],"related_works":["https://openalex.org/W2739612537","https://openalex.org/W2349174696","https://openalex.org/W2360241746","https://openalex.org/W4313041667","https://openalex.org/W2767599893","https://openalex.org/W2381572297","https://openalex.org/W4388070314","https://openalex.org/W2106741186","https://openalex.org/W3192036299","https://openalex.org/W2368890809"],"abstract_inverted_index":{"We":[0,112,129],"have":[1],"implemented":[2],"a":[3,17,36],"technique":[4,15],"for":[5,31,116],"analyzing":[6,117],"and":[7,22,77,118,144],"characterizing":[8],"the":[9,32,40,45,55,83,92,107,114,132,135],"textures":[10,21,66,98,120,138],"in":[11,39],"medical":[12],"images.":[13,111],"This":[14,86],"generates":[16],"list":[18],"of":[19,34,44,57,64,75,95,106,110,134,146],"characteristic":[20],"sorts":[23],"them":[24],"from":[25],"most":[26,136],"important":[27,30],"to":[28,71,104],"least":[29],"task":[33,147],"detecting":[35],"specific":[37],"signal":[38],"image.":[41],"The":[42,61],"effects":[43],"human-visual":[46],"system":[47],"can":[48,67,126],"be":[49,68,127],"incorporated":[50],"into":[51],"this":[52],"method":[53,115],"through":[54],"use":[56],"an":[58],"eye":[59],"filter.":[60],"final":[62],"set":[63,94,109],"sorted":[65],"quickly":[69],"utilized":[70],"analyze":[72],"new":[73,93],"sets":[74],"images":[76,96],"make":[78,140],"comparison":[79],"regarding":[80],"performance":[81,148],"on":[82,122],"same":[84],"task.":[85],"analysis":[87],"is":[88],"based":[89,121],"upon":[90],"whether":[91],"contains":[97],"that":[99,105,139],"are":[100,149],"similar":[101],"or":[102],"dissimilar":[103],"original":[108],"present":[113],"sorting":[119],"how":[123],"well":[124],"signals":[125],"distinguished.":[128],"also":[130],"discuss":[131],"importance":[133],"\"obscuring\"":[137],"signal-detection":[141],"difficult.":[142],"Results":[143],"comparisons":[145],"presented.":[150]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
