{"id":"https://openalex.org/W2544811972","doi":"https://doi.org/10.1109/acssc.2012.6489080","title":"Implicit Gibbs prior models for tomographic reconstruction","display_name":"Implicit Gibbs prior models for tomographic reconstruction","publication_year":2012,"publication_date":"2012-11-01","ids":{"openalex":"https://openalex.org/W2544811972","doi":"https://doi.org/10.1109/acssc.2012.6489080","mag":"2544811972"},"language":"en","primary_location":{"id":"doi:10.1109/acssc.2012.6489080","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2012.6489080","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)","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/A5051636340","display_name":"Pengchong Jin","orcid":null},"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":true,"raw_author_name":"Pengchong Jin","raw_affiliation_strings":["School of ECE, Purdue University, West Lafayette, IN, 47907, USA","School of ECE, Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"School of ECE, Purdue University, West Lafayette, IN, 47907, USA","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"School of ECE, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047552045","display_name":"Eri Haneda","orcid":"https://orcid.org/0000-0003-2660-9028"},"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":"Eri Haneda","raw_affiliation_strings":["School of ECE, Purdue University, West Lafayette, IN, 47907, USA","School of ECE, Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"School of ECE, Purdue University, West Lafayette, IN, 47907, USA","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"School of ECE, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"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 A. Bouman","raw_affiliation_strings":["School of ECE, Purdue University, West Lafayette, IN, 47907, USA","School of ECE, Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"School of ECE, Purdue University, West Lafayette, IN, 47907, USA","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"School of ECE, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5051636340"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":0.9703,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.78247431,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"613","last_page":"616"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9995999932289124,"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":0.9995999932289124,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9993000030517578,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9975000023841858,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6824914813041687},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.6083198189735413},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5700045824050903},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5322195291519165},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5209949612617493},{"id":"https://openalex.org/keywords/conditional-probability-distribution","display_name":"Conditional probability distribution","score":0.5209780335426331},{"id":"https://openalex.org/keywords/tomographic-reconstruction","display_name":"Tomographic reconstruction","score":0.5002133846282959},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.45971301198005676},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45320630073547363},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.43843579292297363},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4155949354171753},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.391169935464859},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27437493205070496},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11904329061508179}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6824914813041687},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.6083198189735413},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5700045824050903},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5322195291519165},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5209949612617493},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.5209780335426331},{"id":"https://openalex.org/C97742081","wikidata":"https://www.wikidata.org/wiki/Q7820109","display_name":"Tomographic reconstruction","level":3,"score":0.5002133846282959},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.45971301198005676},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45320630073547363},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.43843579292297363},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4155949354171753},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.391169935464859},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27437493205070496},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11904329061508179},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acssc.2012.6489080","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2012.6489080","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1960682387","https://openalex.org/W2003624223","https://openalex.org/W2024548281","https://openalex.org/W2114220616","https://openalex.org/W2142419873","https://openalex.org/W2153663612","https://openalex.org/W2166887721","https://openalex.org/W2168668658","https://openalex.org/W6677388911"],"related_works":["https://openalex.org/W2072169887","https://openalex.org/W4386272753","https://openalex.org/W2982317495","https://openalex.org/W2066238105","https://openalex.org/W2088308468","https://openalex.org/W170151271","https://openalex.org/W2017732498","https://openalex.org/W2137532034","https://openalex.org/W2947117330","https://openalex.org/W2295596929"],"abstract_inverted_index":{"Bayesian":[0],"model-based":[1],"inversion":[2],"has":[3],"been":[4],"applied":[5],"to":[6,34,63,76,91,119],"many":[7],"applications,":[8],"such":[9],"as":[10],"tomographic":[11,61,169],"reconstructions.":[12],"However,":[13],"one":[14],"limitation":[15],"of":[16,31,70,84,96,126,171],"these":[17],"methods":[18,50,167],"is":[19,75,117],"that":[20,148,176],"prior":[21,48,162],"models":[22,125,163],"are":[23,28],"quite":[24],"simple;":[25],"so":[26],"they":[27],"not":[29],"capable":[30],"being":[32],"trained":[33,111],"statistically":[35],"represent":[36],"subtle":[37],"detail":[38],"in":[39,59,136],"images.":[40,172],"In":[41,132],"this":[42,134],"paper,":[43],"we":[44],"demonstrate":[45],"how":[46],"novel":[47],"modeling":[49],"based":[51],"on":[52,112],"implicit":[53,72],"Gibbs":[54,73,99],"distributions":[55],"can":[56,109,180],"be":[57,110],"used":[58],"MAP":[60],"reconstruction":[62,170],"improve":[64],"reconstructed":[65],"image":[66,79],"quality.":[67],"The":[68],"concept":[69],"the":[71,78,81,97,102,106,155,177],"distribution":[74,83,108],"model":[77],"using":[80],"conditional":[82,103,107],"each":[85],"pixel":[86],"given":[87],"its":[88],"neighbors":[89],"and":[90,123,164],"construct":[92],"a":[93,113,137,146],"local":[94],"approximation":[95],"true":[98],"energy":[100],"from":[101],"distribution.":[104],"Since":[105],"specific":[114],"dataset,":[115],"it":[116,143],"possible":[118],"obtain":[120],"more":[121],"precise":[122],"expressive":[124],"images":[127],"which":[128],"capture":[129],"unique":[130],"structures.":[131],"practice,":[133],"results":[135,153,174],"spatially":[138],"adaptive":[139],"MRF":[140,161],"model,":[141],"but":[142],"also":[144],"provides":[145],"framework":[147],"assures":[149],"convergence.":[150],"We":[151],"present":[152],"comparing":[154],"proposed":[156,178],"method":[157,179],"with":[158],"both":[159],"state-of-the-art":[160],"K-SVD":[165],"dictionary-based":[166],"for":[168],"Simulation":[173],"indicate":[175],"achieve":[181],"higher":[182],"resolution":[183],"recovery.":[184]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}