{"id":"https://openalex.org/W1978489724","doi":"https://doi.org/10.1137/100798181","title":"A Regularized Gauss\u2013Newton Trust Region Approach to Imaging in Diffuse Optical Tomography","display_name":"A Regularized Gauss\u2013Newton Trust Region Approach to Imaging in Diffuse Optical Tomography","publication_year":2011,"publication_date":"2011-01-01","ids":{"openalex":"https://openalex.org/W1978489724","doi":"https://doi.org/10.1137/100798181","mag":"1978489724"},"language":"en","primary_location":{"id":"doi:10.1137/100798181","is_oa":false,"landing_page_url":"https://doi.org/10.1137/100798181","pdf_url":null,"source":{"id":"https://openalex.org/S165512578","display_name":"SIAM Journal on Scientific Computing","issn_l":"1064-8275","issn":["1064-8275","1095-7197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Scientific Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://vtechworks.lib.vt.edu/bitstreams/ab5d80d7-55be-4bcc-89bf-87044eadacf0/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002320696","display_name":"Eric de Sturler","orcid":"https://orcid.org/0000-0002-9412-9360"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Eric de Sturler","raw_affiliation_strings":["[email\u00a0protected]#TAB#"],"affiliations":[{"raw_affiliation_string":"[email\u00a0protected]#TAB#","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041916316","display_name":"Misha E. Kilmer","orcid":"https://orcid.org/0000-0003-4249-4742"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Misha E. Kilmer","raw_affiliation_strings":["misha.kilmer@tufts.edu#TAB#"],"affiliations":[{"raw_affiliation_string":"misha.kilmer@tufts.edu#TAB#","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5002320696"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.10038119,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"33","issue":"5","first_page":"3057","last_page":"3086"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","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/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9995999932289124,"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/T11778","display_name":"Electrical and Bioimpedance Tomography","score":0.984499990940094,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/mathematics","display_name":"Mathematics","score":0.6820813417434692},{"id":"https://openalex.org/keywords/trust-region","display_name":"Trust region","score":0.656170666217804},{"id":"https://openalex.org/keywords/jacobian-matrix-and-determinant","display_name":"Jacobian matrix and determinant","score":0.6245641112327576},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.5874035358428955},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.58399897813797},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4817212224006653},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.46424874663352966},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.4521392583847046},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.42092037200927734},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.36859703063964844},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.35831713676452637},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.22865012288093567},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.15223556756973267},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.114452064037323}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6820813417434692},{"id":"https://openalex.org/C89109886","wikidata":"https://www.wikidata.org/wiki/Q1535924","display_name":"Trust region","level":3,"score":0.656170666217804},{"id":"https://openalex.org/C200331156","wikidata":"https://www.wikidata.org/wiki/Q506041","display_name":"Jacobian matrix and determinant","level":2,"score":0.6245641112327576},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.5874035358428955},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.58399897813797},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4817212224006653},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.46424874663352966},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.4521392583847046},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.42092037200927734},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36859703063964844},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.35831713676452637},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.22865012288093567},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.15223556756973267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.114452064037323},{"id":"https://openalex.org/C178635117","wikidata":"https://www.wikidata.org/wiki/Q747499","display_name":"RADIUS","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1137/100798181","is_oa":false,"landing_page_url":"https://doi.org/10.1137/100798181","pdf_url":null,"source":{"id":"https://openalex.org/S165512578","display_name":"SIAM Journal on Scientific Computing","issn_l":"1064-8275","issn":["1064-8275","1095-7197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Scientific Computing","raw_type":"journal-article"},{"id":"pmh:oai:vtechworks.lib.vt.edu:10919/48157","is_oa":true,"landing_page_url":"http://hdl.handle.net/10919/48157","pdf_url":"https://vtechworks.lib.vt.edu/bitstreams/ab5d80d7-55be-4bcc-89bf-87044eadacf0/download","source":{"id":"https://openalex.org/S4306400248","display_name":"VTechWorks (Virginia Tech)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I859038795","host_organization_name":"Virginia Tech","host_organization_lineage":["https://openalex.org/I859038795"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:vtechworks.lib.vt.edu:10919/48157","is_oa":true,"landing_page_url":"http://hdl.handle.net/10919/48157","pdf_url":"https://vtechworks.lib.vt.edu/bitstreams/ab5d80d7-55be-4bcc-89bf-87044eadacf0/download","source":{"id":"https://openalex.org/S4306400248","display_name":"VTechWorks (Virginia Tech)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I859038795","host_organization_name":"Virginia Tech","host_organization_lineage":["https://openalex.org/I859038795"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2645536530","display_name":"Inverse Scattering Models and Algorithms for Functional Brain Imaging with Diffuse Optical Wavefields","funder_award_id":"0139968","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6080226867","display_name":null,"funder_award_id":"DMR-0325939","funder_id":"https://openalex.org/F4320337367","funder_display_name":"Division of Materials Research"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G918369032","display_name":"Collaborative Research:     Tuning Libraries to Effectively Exploit the Memory Heirarchy","funder_award_id":"0342559","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337367","display_name":"Division of Materials Research","ror":"https://ror.org/01pc7k308"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W1978489724.pdf","grobid_xml":"https://content.openalex.org/works/W1978489724.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W152981002","https://openalex.org/W1603753160","https://openalex.org/W1969808883","https://openalex.org/W1971059404","https://openalex.org/W1972054485","https://openalex.org/W1978429862","https://openalex.org/W1990381576","https://openalex.org/W2004162158","https://openalex.org/W2013321956","https://openalex.org/W2015000924","https://openalex.org/W2017714771","https://openalex.org/W2018624971","https://openalex.org/W2019082603","https://openalex.org/W2029277933","https://openalex.org/W2033106066","https://openalex.org/W2055793481","https://openalex.org/W2057811942","https://openalex.org/W2061404902","https://openalex.org/W2068484625","https://openalex.org/W2093919938","https://openalex.org/W2114424556","https://openalex.org/W2126096288","https://openalex.org/W2140064412","https://openalex.org/W2161169693","https://openalex.org/W2336071066","https://openalex.org/W2798909945","https://openalex.org/W3029645440","https://openalex.org/W3121468015"],"related_works":["https://openalex.org/W2051058708","https://openalex.org/W154868527","https://openalex.org/W1494268238","https://openalex.org/W1983207144","https://openalex.org/W2490706771","https://openalex.org/W2480116122","https://openalex.org/W1976468483","https://openalex.org/W1600402929","https://openalex.org/W2145886382","https://openalex.org/W2027553280"],"abstract_inverted_index":{"We":[0,257],"present":[1],"a":[2,85,190,196,266,296],"new":[3,275],"algorithm":[4,108,125,137,233,261,276],"for":[5,45,111,129,166],"the":[6,39,141,155,169,172,176,179,183,202,228,235,274,283],"solution":[7],"of":[8,41,89,144,154,171,214],"nonlinear":[9],"least":[10],"squares":[11],"problems":[12,17,76,96,132],"arising":[13],"from":[14,38,240],"parameterized":[15],"imaging":[16,115,285],"with":[18,117,133,287],"diffuse":[19],"optical":[20],"tomographic":[21],"data":[22],"[D.":[23],"Boas":[24],"et":[25,50],"al.,":[26,51],"IEEE":[27],"Signal":[28],"Process.":[29],"Mag.,":[30],"18":[31],"(2001),":[32],"pp.":[33,56,73],"57\u201375].":[34],"The":[35,136,163,193],"parameterization":[36],"arises":[37],"use":[40],"parametric":[42,288],"level":[43,289],"sets":[44],"regularization":[46],"[M.":[47],"E.":[48,61,64],"Kilmer":[49],"Proc.":[52],"SPIE,":[53],"5559":[54],"(2004),":[55],"381\u2013391],":[57],"[A.":[58,241],"Aghasi,":[59],"M.":[60,246],"Kilmer,":[62],"and":[63,91,99,146,175,218,248,291],"L.":[65,250],"Miller,":[66],"SIAM":[67],"J.":[68],"Imaging":[69],"Sci.,":[70],"4":[71],"(2011),":[72],"618\u2013650].":[74],"Such":[75],"lead":[77],"to":[78,126,139,178,187,200,224,227,265,282],"Jacobians":[79],"that":[80,102,259,273],"have":[81,97],"relatively":[82,86],"few":[83],"columns,":[84],"modest":[87],"number":[88,143],"rows,":[90],"are":[92,103],"ill-conditioned.":[93],"Moreover,":[94],"such":[95],"function":[98,145,174],"Jacobian":[100,147],"evaluations":[101,148],"computationally":[104],"expensive.":[105],"Our":[106,232,269],"optimization":[107],"is":[109,195,262],"appropriate":[110],"any":[112],"inverse":[113],"or":[114,161],"problem":[116,286],"those":[118],"characteristics.":[119],"In":[120],"fact,":[121],"we":[122,206],"expect":[123],"our":[124,260],"be":[127,159,188,222],"effective":[128],"more":[130],"general":[131],"ill-conditioned":[134],"Jacobians.":[135],"aims":[138],"minimize":[140],"total":[142],"by":[149,295],"analyzing":[150],"which":[151],"spectral":[152],"components":[153,211,220],"Gauss\u2013Newton":[156],"direction":[157,186],"should":[158],"discarded":[160],"damped.":[162],"analysis":[164],"considers":[165],"each":[167],"component":[168],"reduction":[170],"objective":[173],"contribution":[177],"search":[180,185,203],"direction,":[181],"restricting":[182],"computed":[184],"within":[189],"trust":[191,229],"region.":[192],"result":[194],"truncated":[197],"SVD-like":[198],"approach":[199],"choosing":[201],"direction.":[204],"However,":[205],"do":[207],"not":[208],"necessarily":[209],"discard":[210],"in":[212],"order":[213],"decreasing":[215],"singular":[216],"value,":[217],"some":[219],"may":[221],"scaled":[223],"maintain":[225],"fidelity":[226],"region":[230],"model.":[231],"uses":[234],"Basic":[236],"Trust":[237],"Region":[238],"Algorithm":[239],"R.":[242],"Conn,":[243],"N.":[244],"I.":[245],"Gould,":[247],"Ph.":[249],"Toint,":[251],"Trust-Region":[252],"Methods,":[253],"SIAM,":[254],"Philadelphia,":[255],"2000].":[256],"prove":[258],"globally":[263],"convergent":[264],"critical":[267],"point.":[268],"numerical":[270],"results":[271],"show":[272],"generally":[277],"outperforms":[278],"competing":[279],"methods":[280],"applied":[281],"DOT":[284],"sets,":[290],"regularly":[292],"does":[293],"so":[294],"significant":[297],"factor.":[298]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":4}],"updated_date":"2026-03-15T09:29:46.208133","created_date":"2025-10-10T00:00:00"}