{"id":"https://openalex.org/W2777029899","doi":"https://doi.org/10.1109/icip.2017.8296949","title":"Performance comparison of Bayesian iterative algorithms for three classes of sparsity enforcing priors with application in computed tomography","display_name":"Performance comparison of Bayesian iterative algorithms for three classes of sparsity enforcing priors with application in computed tomography","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2777029899","doi":"https://doi.org/10.1109/icip.2017.8296949","mag":"2777029899"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296949","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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/A5056722645","display_name":"Mircea Dumitru","orcid":"https://orcid.org/0000-0002-1749-4831"},"institutions":[{"id":"https://openalex.org/I4210107720","display_name":"CentraleSup\u00e9lec","ror":"https://ror.org/019tcpt25","country_code":"FR","type":"facility","lineage":["https://openalex.org/I277688954","https://openalex.org/I4210107720"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mircea Dumitru","raw_affiliation_strings":["Laboratoire des signaux et syst\u00e8mes, CentraleSup\u00e9lec, Gif-sur-Yvette, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratoire des signaux et syst\u00e8mes, CentraleSup\u00e9lec, Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I4210107720"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108047222","display_name":"Li Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210107720","display_name":"CentraleSup\u00e9lec","ror":"https://ror.org/019tcpt25","country_code":"FR","type":"facility","lineage":["https://openalex.org/I277688954","https://openalex.org/I4210107720"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Li Wang","raw_affiliation_strings":["Laboratoire des signaux et syst\u00e8mes, CentraleSup\u00e9lec, Gif-sur-Yvette, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratoire des signaux et syst\u00e8mes, CentraleSup\u00e9lec, Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I4210107720"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082573179","display_name":"Nicolas Gac","orcid":"https://orcid.org/0000-0001-6981-0368"},"institutions":[{"id":"https://openalex.org/I4210107720","display_name":"CentraleSup\u00e9lec","ror":"https://ror.org/019tcpt25","country_code":"FR","type":"facility","lineage":["https://openalex.org/I277688954","https://openalex.org/I4210107720"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Nicolas Gac","raw_affiliation_strings":["Laboratoire des signaux et syst\u00e8mes, CentraleSup\u00e9lec, Gif-sur-Yvette, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratoire des signaux et syst\u00e8mes, CentraleSup\u00e9lec, Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I4210107720"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041990954","display_name":"Ali Mohammad\u2010Djafari","orcid":"https://orcid.org/0000-0003-0678-7759"},"institutions":[{"id":"https://openalex.org/I4210107720","display_name":"CentraleSup\u00e9lec","ror":"https://ror.org/019tcpt25","country_code":"FR","type":"facility","lineage":["https://openalex.org/I277688954","https://openalex.org/I4210107720"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Ali Mohammad-Djafari","raw_affiliation_strings":["Laboratoire des signaux et syst\u00e8mes, CentraleSup\u00e9lec, Gif-sur-Yvette, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratoire des signaux et syst\u00e8mes, CentraleSup\u00e9lec, Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I4210107720"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1976,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.8384237,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3580","last_page":"3584"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9954000115394592,"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/prior-probability","display_name":"Prior probability","score":0.8282432556152344},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.7194671630859375},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6242440938949585},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6141406893730164},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5862457156181335},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5379462838172913},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.5216420292854309},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5132974982261658},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.49813294410705566},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4825443625450134},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.4740833044052124},{"id":"https://openalex.org/keywords/tomography","display_name":"Tomography","score":0.4112173318862915},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40339195728302},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38021495938301086},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36914026737213135},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13937291502952576},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.10578286647796631}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.8282432556152344},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.7194671630859375},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6242440938949585},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6141406893730164},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5862457156181335},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5379462838172913},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.5216420292854309},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5132974982261658},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.49813294410705566},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4825443625450134},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.4740833044052124},{"id":"https://openalex.org/C163716698","wikidata":"https://www.wikidata.org/wiki/Q841267","display_name":"Tomography","level":2,"score":0.4112173318862915},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40339195728302},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38021495938301086},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36914026737213135},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13937291502952576},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.10578286647796631},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2017.8296949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296949","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","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":16,"referenced_works":["https://openalex.org/W1579338905","https://openalex.org/W1579925870","https://openalex.org/W2030835564","https://openalex.org/W2039117831","https://openalex.org/W2048837324","https://openalex.org/W2079256353","https://openalex.org/W2101946599","https://openalex.org/W2137449599","https://openalex.org/W2145768101","https://openalex.org/W2152498207","https://openalex.org/W2161429744","https://openalex.org/W2164129707","https://openalex.org/W2166087152","https://openalex.org/W2294150140","https://openalex.org/W2404009085","https://openalex.org/W2407641597"],"related_works":["https://openalex.org/W1839961359","https://openalex.org/W2075146114","https://openalex.org/W2100805585","https://openalex.org/W1967979023","https://openalex.org/W2107692390","https://openalex.org/W2107386309","https://openalex.org/W2545869789","https://openalex.org/W2141090006","https://openalex.org/W1964555484","https://openalex.org/W3048932468"],"abstract_inverted_index":{"The":[0,40],"piecewise":[1],"constant":[2],"or":[3],"homogeneous":[4],"image":[5],"reconstruction":[6,78],"in":[7,69,82],"the":[8,22,55,61,64,74],"context":[9],"of":[10,25,63,71],"X-ray":[11],"Computed":[12,83],"Tomography":[13],"is":[14,28,67],"considered":[15],"within":[16],"a":[17],"Bayesian":[18],"approach.":[19],"More":[20],"precisely,":[21],"sparse":[23],"transformation":[24],"such":[26],"images":[27],"modelled":[29],"with":[30],"heavy":[31],"tailed":[32],"distributions":[33],"expressed":[34],"as":[35],"Normal":[36],"variance":[37],"mixtures":[38],"marginals.":[39],"derived":[41],"iterative":[42],"algorithms":[43],"(via":[44],"Joint":[45],"Maximum":[46],"A":[47],"Posteriori)":[48],"have":[49],"identical":[50],"updating":[51],"expressions,":[52],"except":[53],"for":[54],"estimated":[56],"variances.":[57],"We":[58],"show":[59],"that":[60],"behaviour":[62],"each":[65],"algorithm":[66],"different":[68],"terms":[70],"sensibility":[72],"to":[73],"model":[75],"selection":[76],"and":[77],"performances":[79],"when":[80],"applied":[81],"Tomography.":[84]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}