{"id":"https://openalex.org/W2165673807","doi":"https://doi.org/10.1109/isbi.2011.5872726","title":"On MR experiment design with quadratic regularization","display_name":"On MR experiment design with quadratic regularization","publication_year":2011,"publication_date":"2011-03-01","ids":{"openalex":"https://openalex.org/W2165673807","doi":"https://doi.org/10.1109/isbi.2011.5872726","mag":"2165673807"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2011.5872726","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2011.5872726","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","raw_type":"proceedings-article"},"type":"conference-paper","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/A5031370363","display_name":"Justin P. Haldar","orcid":"https://orcid.org/0000-0002-1838-0211"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Justin P. Haldar","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Beckman Institute, University of Illinois, Urbana-Champaign, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Beckman Institute, University of Illinois, Urbana-Champaign, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019294923","display_name":"Zhi\u2010Pei Liang","orcid":"https://orcid.org/0000-0003-4586-3056"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhi-Pei Liang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Beckman Institute, University of Illinois, Urbana-Champaign, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Beckman Institute, University of Illinois, Urbana-Champaign, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1676","last_page":"1679"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9998000264167786,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9998000264167786,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9993000030517578,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9980999827384949,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.8043244481086731},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.6013210415840149},{"id":"https://openalex.org/keywords/data-acquisition","display_name":"Data acquisition","score":0.6010915040969849},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5911821722984314},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5894320607185364},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.5484415888786316},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4782649278640747},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.43507134914398193},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41866976022720337},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.358102023601532},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35679152607917786},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2686479091644287}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.8043244481086731},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.6013210415840149},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.6010915040969849},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5911821722984314},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5894320607185364},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.5484415888786316},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4782649278640747},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.43507134914398193},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41866976022720337},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.358102023601532},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35679152607917786},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2686479091644287},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2011.5872726","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2011.5872726","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","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":16,"referenced_works":["https://openalex.org/W1009118580","https://openalex.org/W1971098481","https://openalex.org/W1999197846","https://openalex.org/W2024971034","https://openalex.org/W2032038095","https://openalex.org/W2049609055","https://openalex.org/W2094441093","https://openalex.org/W2101675075","https://openalex.org/W2107906890","https://openalex.org/W2111422394","https://openalex.org/W2111460811","https://openalex.org/W2122328164","https://openalex.org/W2133307020","https://openalex.org/W2163056067","https://openalex.org/W2477033167","https://openalex.org/W2990836033"],"related_works":["https://openalex.org/W4372306488","https://openalex.org/W4210912696","https://openalex.org/W2075579715","https://openalex.org/W2946070927","https://openalex.org/W2388668112","https://openalex.org/W2104766064","https://openalex.org/W2069972811","https://openalex.org/W2160652815","https://openalex.org/W2623997598","https://openalex.org/W3126543146"],"abstract_inverted_index":{"The":[0],"design":[1,97],"of":[2,81,86,98,104],"MRI":[3],"experiments":[4,100],"represents":[5],"a":[6,61],"trade-off":[7],"between":[8],"acquisition":[9,18,31,63],"time,":[10],"signal-to-noise":[11],"ratio":[12],"(SNR),":[13],"and":[14,20,101],"resolution.":[15,46],"For":[16],"fixed":[17],"time":[19],"reconstruction":[21],"resolution,":[22],"it":[23],"has":[24],"been":[25],"widely":[26],"believed":[27],"that":[28,60],"the":[29,43,79,95,102],"optimal":[30],"strategy":[32],"is":[33,50],"to":[34,73,91],"avoid":[35],"collecting":[36],"k-space":[37],"data":[38],"at":[39],"frequencies":[40],"higher":[41],"than":[42],"nominal":[44],"image":[45],"While":[47],"this":[48,58,87],"belief":[49],"true":[51],"under":[52],"certain":[53],"metrics,":[54],"we":[55],"observe":[56],"in":[57],"work":[59],"high-resolution":[62],"strategy,":[64,71],"combined":[65],"with":[66],"an":[67],"appropriate":[68],"linear":[69],"filtering/regularization":[70],"leads":[72,90],"significantly":[74],"improved":[75,96],"SNR/resolution":[76],"efficiency":[77],"for":[78,94],"majority":[80],"common":[82],"resolution":[83],"metrics.":[84],"Analysis":[85],"surprising":[88],"result":[89],"practical":[92],"methods":[93],"imaging":[99],"selection":[103],"efficient":[105],"quadratic":[106],"regularization":[107],"penalties.":[108]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
