{"id":"https://openalex.org/W4220862702","doi":"https://doi.org/10.1117/12.2613050","title":"Optimizing model observer performance in learning-based CT reconstruction","display_name":"Optimizing model observer performance in learning-based CT reconstruction","publication_year":2022,"publication_date":"2022-03-31","ids":{"openalex":"https://openalex.org/W4220862702","doi":"https://doi.org/10.1117/12.2613050"},"language":"en","primary_location":{"id":"doi:10.1117/12.2613050","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2613050","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2022: 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/A5020368316","display_name":"Greg Ongie","orcid":"https://orcid.org/0000-0003-1417-3925"},"institutions":[{"id":"https://openalex.org/I102461120","display_name":"Marquette University","ror":"https://ror.org/04gr4te78","country_code":"US","type":"education","lineage":["https://openalex.org/I102461120"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Gregory Ongie","raw_affiliation_strings":["Marquette Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Marquette Univ. (United States)","institution_ids":["https://openalex.org/I102461120"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035273354","display_name":"Emil Y. Sidky","orcid":"https://orcid.org/0000-0002-6951-2456"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Emil Y. Sidky","raw_affiliation_strings":["Univ. of Chicago  (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Chicago  (United States)","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010707434","display_name":"Ingrid Reiser","orcid":"https://orcid.org/0000-0002-2047-2190"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ingrid S. Reiser","raw_affiliation_strings":["Univ. of Chicago (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Chicago (United States)","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101465418","display_name":"Xiaochuan Pan","orcid":"https://orcid.org/0000-0002-3074-9771"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaochuan Pan","raw_affiliation_strings":["Univ. of Chicago  (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Chicago  (United States)","institution_ids":["https://openalex.org/I40347166"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5020368316"],"corresponding_institution_ids":["https://openalex.org/I102461120"],"apc_list":null,"apc_paid":null,"fwci":0.8666,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.70647024,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"6","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9994999766349792,"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/T10844","display_name":"Radiation Dose and Imaging","score":0.9979000091552734,"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":0.730390727519989},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.700685441493988},{"id":"https://openalex.org/keywords/observer","display_name":"Observer (physics)","score":0.6129409074783325},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6024433374404907},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5352097153663635},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5202059149742126},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.4808793365955353},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4682392179965973},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.46767839789390564},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4433706998825073},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44173532724380493},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4240914583206177},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3932321071624756},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.2512747049331665},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16706201434135437},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07935434579849243}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.730390727519989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.700685441493988},{"id":"https://openalex.org/C2780704645","wikidata":"https://www.wikidata.org/wiki/Q9251458","display_name":"Observer (physics)","level":2,"score":0.6129409074783325},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6024433374404907},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5352097153663635},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5202059149742126},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.4808793365955353},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4682392179965973},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.46767839789390564},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4433706998825073},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44173532724380493},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4240914583206177},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3932321071624756},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2512747049331665},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16706201434135437},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07935434579849243},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"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/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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1117/12.2613050","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2613050","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2022: Image Perception, Observer Performance, and Technology Assessment","raw_type":"proceedings-article"},{"id":"pmh:oai:epublications.marquette.edu:math_fac-1138","is_oa":false,"landing_page_url":"https://epublications.marquette.edu/math_fac/139","pdf_url":null,"source":{"id":"https://openalex.org/S4306401682","display_name":"e-Publications@Marquette (Marquette University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I102461120","host_organization_name":"Marquette University","host_organization_lineage":["https://openalex.org/I102461120"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Mathematical and Statistical Science Faculty Research and Publications","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2041066345","https://openalex.org/W2574952845","https://openalex.org/W3092095714","https://openalex.org/W4231200252","https://openalex.org/W6639824700","https://openalex.org/W6786352824"],"related_works":["https://openalex.org/W2786391746","https://openalex.org/W2097754634","https://openalex.org/W3132346564","https://openalex.org/W2991483587","https://openalex.org/W2914559142","https://openalex.org/W4381430104","https://openalex.org/W2152405644","https://openalex.org/W4226059458","https://openalex.org/W2995102745","https://openalex.org/W1990237101"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2,30],"used":[3],"for":[4,46],"reconstructing":[5],"sparse-view":[6,85],"CT":[7,87],"data":[8],"are":[9,35,44],"typically":[10],"trained":[11,31],"by":[12,61],"minimizing":[13],"a":[14,24,56],"pixel-":[15],"wise":[16],"mean-squared":[17],"error":[18],"or":[19],"similar":[20],"loss":[21,59],"function":[22],"over":[23],"set":[25],"of":[26,70,83],"training":[27,58],"images.":[28],"However,":[29],"with":[32,96],"such":[33],"losses":[34],"prone":[36],"to":[37,66],"wipe":[38],"out":[39],"small,":[40],"low-contrast":[41],"features":[42],"that":[43],"critical":[45],"screening":[47],"and":[48,89],"diagnosis.":[49],"To":[50],"remedy":[51],"this":[52],"issue,":[53],"we":[54],"introduce":[55],"novel":[57],"inspired":[60],"the":[62,68,74,81,97],"model":[63],"observer":[64],"framework":[65],"enhance":[67],"detectability":[69,95],"weak":[71],"signals":[72],"in":[73,93],"reconstructions.":[75],"We":[76],"evaluate":[77],"our":[78],"approach":[79],"on":[80],"reconstruction":[82],"synthetic":[84],"breast":[86],"data,":[88],"demonstrate":[90],"an":[91],"improvement":[92],"signal":[94],"proposed":[98],"loss.":[99]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
