{"id":"https://openalex.org/W2086685030","doi":"https://doi.org/10.1117/12.2048204","title":"Statistical x-ray computed tomography imaging from photon-starved measurements","display_name":"Statistical x-ray computed tomography imaging from photon-starved measurements","publication_year":2014,"publication_date":"2014-03-07","ids":{"openalex":"https://openalex.org/W2086685030","doi":"https://doi.org/10.1117/12.2048204","mag":"2086685030"},"language":"en","primary_location":{"id":"doi:10.1117/12.2048204","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2048204","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","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/A5032706978","display_name":"Zhiqian Chang","orcid":"https://orcid.org/0000-0003-2780-4407"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhiqian Chang","raw_affiliation_strings":["Univ. of Notre Dame (United States)","University of Notre Dame United States"],"affiliations":[{"raw_affiliation_string":"Univ. of Notre Dame (United States)","institution_ids":["https://openalex.org/I107639228"]},{"raw_affiliation_string":"University of Notre Dame United States","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033755512","display_name":"Ruoqiao Zhang","orcid":"https://orcid.org/0000-0002-5511-3390"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruoqiao Zhang","raw_affiliation_strings":["Purdue Univ. (United States)","#N##TAB##TAB##TAB##TAB# Purdue University, United States#N##TAB##TAB##TAB#"],"affiliations":[{"raw_affiliation_string":"Purdue Univ. (United States)","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"#N##TAB##TAB##TAB##TAB# Purdue University, United States#N##TAB##TAB##TAB#","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109296991","display_name":"Jean\u2010Baptiste Thibault","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jean-Baptiste Thibault","raw_affiliation_strings":["GE Healthcare (United States)"],"affiliations":[{"raw_affiliation_string":"GE Healthcare (United States)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110231549","display_name":"K. Sauer","orcid":null},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ken Sauer","raw_affiliation_strings":["Univ. of Notre Dame (United States)","University of Notre Dame United States"],"affiliations":[{"raw_affiliation_string":"Univ. of Notre Dame (United States)","institution_ids":["https://openalex.org/I107639228"]},{"raw_affiliation_string":"University of Notre Dame United States","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056657991","display_name":"Charles A. Bouman","orcid":"https://orcid.org/0000-0001-8504-0383"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Charles Bouman","raw_affiliation_strings":["Purdue Univ. (United States)","#N##TAB##TAB##TAB##TAB# Purdue University, United States#N##TAB##TAB##TAB#"],"affiliations":[{"raw_affiliation_string":"Purdue Univ. (United States)","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"#N##TAB##TAB##TAB##TAB# Purdue University, United States#N##TAB##TAB##TAB#","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5032706978"],"corresponding_institution_ids":["https://openalex.org/I107639228"],"apc_list":null,"apc_paid":null,"fwci":2.49356838,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.87651888,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"9020","issue":null,"first_page":"90200G","last_page":"90200G"},"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":0.9998000264167786,"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":0.9976000189781189,"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/statistical-noise","display_name":"Statistical noise","score":0.7348995208740234},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7049446702003479},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6535550355911255},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.5973395109176636},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5871940851211548},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5856865048408508},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5470805764198303},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5083231329917908},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5063701868057251},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5047372579574585},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4952777922153473},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4843929409980774},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45938828587532043},{"id":"https://openalex.org/keywords/single-photon-emission-computed-tomography","display_name":"Single-photon emission computed tomography","score":0.43453627824783325},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.42101961374282837},{"id":"https://openalex.org/keywords/tomography","display_name":"Tomography","score":0.42016854882240295},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.41896945238113403},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.4100545346736908},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3866933584213257},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34214919805526733},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.33314719796180725},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2962779104709625},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.23650023341178894},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.20497259497642517},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1550072431564331},{"id":"https://openalex.org/keywords/nuclear-medicine","display_name":"Nuclear medicine","score":0.12453725934028625},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11489194631576538}],"concepts":[{"id":"https://openalex.org/C128197687","wikidata":"https://www.wikidata.org/wiki/Q5477515","display_name":"Statistical noise","level":2,"score":0.7348995208740234},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7049446702003479},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6535550355911255},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.5973395109176636},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5871940851211548},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5856865048408508},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5470805764198303},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5083231329917908},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5063701868057251},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5047372579574585},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4952777922153473},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4843929409980774},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45938828587532043},{"id":"https://openalex.org/C2780441642","wikidata":"https://www.wikidata.org/wiki/Q849737","display_name":"Single-photon emission computed tomography","level":2,"score":0.43453627824783325},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.42101961374282837},{"id":"https://openalex.org/C163716698","wikidata":"https://www.wikidata.org/wiki/Q841267","display_name":"Tomography","level":2,"score":0.42016854882240295},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.41896945238113403},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.4100545346736908},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3866933584213257},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34214919805526733},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.33314719796180725},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2962779104709625},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.23650023341178894},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.20497259497642517},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1550072431564331},{"id":"https://openalex.org/C2989005","wikidata":"https://www.wikidata.org/wiki/Q214963","display_name":"Nuclear medicine","level":1,"score":0.12453725934028625},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11489194631576538},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2048204","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2048204","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1573432006","https://openalex.org/W1965528481","https://openalex.org/W2003624223","https://openalex.org/W2049909233","https://openalex.org/W2079819437","https://openalex.org/W2090475827","https://openalex.org/W2122345610","https://openalex.org/W2142419873","https://openalex.org/W2154129661","https://openalex.org/W2157099732","https://openalex.org/W6634407178","https://openalex.org/W6641518009","https://openalex.org/W6670463771"],"related_works":["https://openalex.org/W2357322570","https://openalex.org/W90581812","https://openalex.org/W2997591215","https://openalex.org/W2227541280","https://openalex.org/W2038232617","https://openalex.org/W2974904990","https://openalex.org/W2081721401","https://openalex.org/W2185567058","https://openalex.org/W1976541673","https://openalex.org/W4389667162"],"abstract_inverted_index":{"Dose":[0],"reduction":[1],"in":[2,13,68],"clinical":[3],"X-ray":[4],"computed":[5],"tomography":[6],"(CT)":[7],"causes":[8],"low":[9],"signal-to-noise":[10],"ratio":[11],"(SNR)":[12],"photonsparse":[14],"situations.":[15],"Statistical":[16],"iterative":[17],"reconstruction":[18],"algorithms":[19],"have":[20],"the":[21,42,65],"advantage":[22],"of":[23,36,41,49,70,79],"retaining":[24],"image":[25,110,129],"quality":[26,130],"while":[27],"reducing":[28],"input":[29],"dosage,":[30],"but":[31,101],"they":[32],"meet":[33],"their":[34],"limits":[35],"practicality":[37],"when":[38],"significant":[39],"portions":[40],"sinogram":[43],"near":[44],"photon":[45,55],"starvation.":[46],"The":[47,90],"corruption":[48],"electronic":[50],"noise":[51],"leads":[52],"to":[53,95],"measured":[54],"counts":[56],"taking":[57],"on":[58,119],"negative":[59],"values,":[60],"posing":[61],"a":[62,115],"problem":[63],"for":[64],"log()":[66],"operation":[67],"preprocessing":[69],"data.":[71],"In":[72],"this":[73],"paper,":[74],"we":[75],"propose":[76],"two":[77],"categories":[78],"projection":[80],"correction":[81],"methods:":[82],"an":[83],"adaptive":[84],"denoising":[85,91],"filter":[86,92],"and":[87,97,107,121],"Bayesian":[88,112],"inference.":[89],"is":[93,114],"easy":[94],"implement":[96],"preserves":[98],"local":[99],"statistics,":[100],"it":[102],"introduces":[103],"correlation":[104],"between":[105],"channels":[106],"may":[108],"affect":[109],"resolution.":[111],"inference":[113],"point-wise":[116],"estimation":[117],"based":[118],"measurements":[120],"prior":[122],"information.":[123],"Both":[124],"approaches":[125],"help":[126],"improve":[127],"diagnostic":[128],"at":[131],"dramatically":[132],"reduced":[133],"dosage.":[134]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}