{"id":"https://openalex.org/W2790216453","doi":"https://doi.org/10.1117/12.2293347","title":"Multi-grid nonlocal techniques for x-ray scatter correction","display_name":"Multi-grid nonlocal techniques for x-ray scatter correction","publication_year":2018,"publication_date":"2018-03-02","ids":{"openalex":"https://openalex.org/W2790216453","doi":"https://doi.org/10.1117/12.2293347","mag":"2790216453"},"language":"en","primary_location":{"id":"doi:10.1117/12.2293347","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2293347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2018: Image Processing","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/A5101973026","display_name":"Yingying Gu","orcid":"https://orcid.org/0000-0002-3802-4361"},"institutions":[{"id":"https://openalex.org/I43579087","display_name":"University of Wisconsin\u2013Milwaukee","ror":"https://ror.org/031q21x57","country_code":"US","type":"education","lineage":["https://openalex.org/I43579087"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yingying Gu","raw_affiliation_strings":["Univ. of Wisconsin-Milwaukee (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Wisconsin-Milwaukee (United States)","institution_ids":["https://openalex.org/I43579087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100433227","display_name":"Jun Zhang","orcid":"https://orcid.org/0000-0002-9647-0941"},"institutions":[{"id":"https://openalex.org/I43579087","display_name":"University of Wisconsin\u2013Milwaukee","ror":"https://ror.org/031q21x57","country_code":"US","type":"education","lineage":["https://openalex.org/I43579087"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Zhang","raw_affiliation_strings":["Univ. of Wisconsin-Milwaukee (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Wisconsin-Milwaukee (United States)","institution_ids":["https://openalex.org/I43579087"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112257855","display_name":"Ping Xue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ping Xue","raw_affiliation_strings":["GE Healthcare (United States)"],"affiliations":[{"raw_affiliation_string":"GE Healthcare (United States)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101973026"],"corresponding_institution_ids":["https://openalex.org/I43579087"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01590002,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"59","last_page":"59"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994999766349792,"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/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.7836923003196716},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.7246077060699463},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.6655313372612},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.645864725112915},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5297544598579407},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.514234721660614},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.489305704832077},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4829092025756836},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4357925057411194},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3355449438095093},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20835062861442566},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08075600862503052}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.7836923003196716},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.7246077060699463},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.6655313372612},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.645864725112915},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5297544598579407},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.514234721660614},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.489305704832077},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4829092025756836},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4357925057411194},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3355449438095093},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20835062861442566},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08075600862503052},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2293347","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2293347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2018: Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1964772475","https://openalex.org/W1983619527","https://openalex.org/W2091494211","https://openalex.org/W2136396015","https://openalex.org/W2137901785","https://openalex.org/W2346276594","https://openalex.org/W2593057843","https://openalex.org/W6673635604","https://openalex.org/W6680349301","https://openalex.org/W6680860766","https://openalex.org/W6704602687","https://openalex.org/W6734265329"],"related_works":["https://openalex.org/W2580650124","https://openalex.org/W4386190339","https://openalex.org/W2968424575","https://openalex.org/W2562263695","https://openalex.org/W2135187896","https://openalex.org/W2147201983","https://openalex.org/W2015518264","https://openalex.org/W2795035211","https://openalex.org/W2160108762","https://openalex.org/W2017034551"],"abstract_inverted_index":{"In":[0,97],"this":[1,55,81],"work,":[2],"we":[3,57],"used":[4,106],"nonlocal":[5,74,115],"priors":[6],"in":[7,31,38,50,72],"a":[8,33,59],"Bayesian":[9],"approach":[10],"for":[11,107],"X-ray":[12],"scatter":[13,100],"correction.":[14],"The":[15],"control":[16],"parameters":[17],"of":[18,94],"our":[19],"algorithms":[20],"such":[21,32],"as":[22],"the":[23,68,73,86,92],"patch":[24],"sizes":[25],"and":[26],"search":[27],"areas":[28],"were":[29],"set":[30],"way":[34],"that":[35,80],"significant":[36],"improvement":[37],"correction":[39,95],"results":[40,77],"can":[41,103],"be":[42,105],"achieved.":[43],"This,":[44],"however,":[45],"led":[46],"to":[47,99],"drastic":[48],"increases":[49],"computation":[51,87],"time.":[52],"To":[53],"solve":[54],"problem,":[56],"developed":[58],"novel":[60],"multi-grid":[61],"technique":[62,82],"based":[63],"on":[64,67],"some":[65],"observations":[66],"matching":[69],"process":[70],"involved":[71],"priors.":[75],"Experimental":[76],"have":[78],"demonstrated":[79],"is":[83,117],"effective,":[84],"accelerating":[85],"time":[88],"significantly":[89],"while":[90],"maintaining":[91],"quality":[93],"results.":[96],"addition":[98],"correction,":[101],"it":[102],"also":[104],"other":[108],"image":[109],"processing":[110],"applications":[111],"where":[112],"fast":[113],"high-dimensional":[114],"filtering":[116],"needed.":[118]},"counts_by_year":[],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}