{"id":"https://openalex.org/W2950814162","doi":"https://doi.org/10.14264/uql.2019.388","title":"Mathematical models for efficient medical electromagnetic tomography","display_name":"Mathematical models for efficient medical electromagnetic tomography","publication_year":2019,"publication_date":"2019-04-29","ids":{"openalex":"https://openalex.org/W2950814162","doi":"https://doi.org/10.14264/uql.2019.388","mag":"2950814162"},"language":"en","primary_location":{"id":"doi:10.14264/uql.2019.388","is_oa":false,"landing_page_url":"https://doi.org/10.14264/uql.2019.388","pdf_url":null,"source":{"id":"https://openalex.org/S7407053192","display_name":"The University of Queensland","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The University of Queensland","raw_type":"dissertation"},"type":"dissertation","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/A5025439781","display_name":"Arman Afsari","orcid":"https://orcid.org/0000-0003-4433-1242"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Arman Afsari","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4433-1242","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5025439781"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9632999897003174,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9632999897003174,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9106000065803528,"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/parametric-statistics","display_name":"Parametric statistics","score":0.6040241718292236},{"id":"https://openalex.org/keywords/stroke","display_name":"Stroke (engine)","score":0.5380795001983643},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.5181875824928284},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.47814738750457764},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44268354773521423},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.4213339686393738},{"id":"https://openalex.org/keywords/neuroimaging","display_name":"Neuroimaging","score":0.4150789976119995},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37544479966163635},{"id":"https://openalex.org/keywords/medical-physics","display_name":"Medical physics","score":0.3682379722595215},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19902506470680237},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19702348113059998},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.11844760179519653}],"concepts":[{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6040241718292236},{"id":"https://openalex.org/C2780645631","wikidata":"https://www.wikidata.org/wiki/Q671554","display_name":"Stroke (engine)","level":2,"score":0.5380795001983643},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.5181875824928284},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.47814738750457764},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44268354773521423},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4213339686393738},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.4150789976119995},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37544479966163635},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.3682379722595215},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19902506470680237},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19702348113059998},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.11844760179519653},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.14264/uql.2019.388","is_oa":false,"landing_page_url":"https://doi.org/10.14264/uql.2019.388","pdf_url":null,"source":{"id":"https://openalex.org/S7407053192","display_name":"The University of Queensland","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The University of Queensland","raw_type":"dissertation"},{"id":"pmh:oai:espace.library.uq.edu.au:UQ:4273f48","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402388","display_name":"Queensland's institutional digital repository (The University of Queensland)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I165143802","host_organization_name":"The University of Queensland","host_organization_lineage":["https://openalex.org/I165143802"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2327340211","https://openalex.org/W2385859805","https://openalex.org/W2027542625","https://openalex.org/W4292199793","https://openalex.org/W2530972254","https://openalex.org/W2282195379","https://openalex.org/W2089784006","https://openalex.org/W2295388821","https://openalex.org/W2102312026","https://openalex.org/W2885663991"],"abstract_inverted_index":{"The":[0,183,227,242,281,320,356,380,431],"World":[1],"Health":[2],"Organization":[3],"defines":[4],"stroke":[5,41,76,85,115,215,395,429],"as":[6,74,141,201,236,301],"the":[7,28,35,40,52,57,84,93,97,163,198,202,214,237,240,261,271,274,287,291,324,330,337,351,362,372,390,402,406,414,428,469,478,482,503],"\u201cneurological":[8],"deficit":[9],"of":[10,49,56,100,132,195,213,239,263,273,374,409,419,427,434,468,485,493,496],"cerebrovascular":[11],"cause":[12],"that":[13,34,44,162,190,204,401],"persists":[14],"beyond":[15],"24":[16,24],"hours":[17,48],"or":[18,87,136,234,254,376],"is":[19,66,79,284,296,303,327],"interrupted":[20],"by":[21,232,252,278,388,421,441,502],"death":[22],"within":[23],"hours\u201d.":[25],"This":[26],"necessitates":[27],"need":[29],"to":[30,81,92,111,125,138,222,344,411,473],"act":[31],"swiftly":[32],"so":[33,161],"treatment":[36,94,415],"process":[37],"can":[38,166,268,367],"reduce":[39],"severity,":[42],"knowing":[43],"after":[45],"around":[46],"six":[47],"symptoms":[50],"onset,":[51],"corresponding":[53,352],"lost":[54],"functions":[55],"brain":[58],"become":[59],"irreversible.":[60],"Such":[61],"a":[62,70,127,142,192,217,224,346,460,465,490],"swift":[63],"act,":[64],"nevertheless,":[65],"currently":[67],"performed":[68],"under":[69],"partial":[71,377],"medical":[72,171,225,275,347,425],"uncertainly,":[73],"no":[75],"monitoring":[77,172,185,200,229,283,389],"tool":[78],"available":[80],"efficiently":[82,412,476],"screen":[83],"\u201cgeometry\u201d":[86],"\u201cparameters\u201d":[88],"and":[89,129,197,315,339,349,354,364,383,392,417,487],"their":[90],"responses":[91],"process.":[95],"Regarding":[96],"potential":[98],"capability":[99,408],"electromagnetic":[101,424,451,471],"tomography":[102,461],"(EMT)":[103],"science,":[104],"some":[105,155,209,495],"efforts":[106],"have":[107,120],"already":[108],"been":[109,123],"undertaken":[110],"utilize":[112],"EMT":[113,160,189,366,385,410],"for":[114,159,445,450],"monitoring.":[116,280],"Nevertheless,":[117],"those":[118],"attempts":[119],"not":[121,247,457,499],"adequately":[122],"successful":[124],"provide":[126,223],"clear":[128],"reliable":[130],"picture":[131],"stroke,":[133,196],"either":[134,370],"geometric":[135,184,243,279,321,365,384],"parametric,":[137],"be":[139,167,368],"regarded":[140],"translational":[143],"imaging":[144,164],"modality.":[145],"In":[146],"this":[147,149,299,435,454],"respect,":[148],"thesis":[150,404,436],"has":[151],"focused":[152],"on":[153,187,207,286,323,329,360],"proposing":[154],"modified":[156],"mathematical":[157,175,358],"formalism":[158],"modality":[165],"potentially":[168],"seated":[169],"in":[170,179,216,260,298,371],"applications.":[173],"These":[174],"models":[176],"are":[177,386,498],"classified":[178],"two":[180],"general":[181,448],"categories:":[182],"based":[186],"global":[188],"provides":[191],"\u201cmedical":[193],"image\u201d":[194],"parametric":[199,228,282,363,382],"approach":[203],"only":[205],"focuses":[206],"updating":[208],"given":[210],"initial":[211,265],"parameters":[212],"\u201cgraph-based\u201d":[218],"format":[219],"(not":[220],"able":[221],"image).":[226],"requires":[230],"initiation":[231,251],"MRI":[233,253],"X-ray":[235],"input":[238],"algorithm.":[241],"monitoring,":[244,322],"however,":[245],"does":[246,456],"necessarily":[248],"require":[249],"an":[250,258,264],"X-ray,":[255],"though":[256],"such":[257],"initiation,":[259],"form":[262,373],"head":[266],"template,":[267],"remarkably":[269],"improve":[270,413],"accuracy":[272],"image":[276,348],"generated":[277],"established":[285,328],"gradient-free":[288,294,309],"optimization,":[289,332],"where":[290,333],"Nelder-Mead":[292],"(NM)":[293],"optimization":[295,318,342],"implemented":[297],"thesis,":[300],"it":[302,463],"usually":[304],"faster":[305],"than":[306],"other":[307,325],"popular":[308],"techniques":[310],"like":[311],"genetic":[312],"algorithm":[313],"(GA)":[314],"particle":[316],"swarm":[317],"(PSO).":[319],"hand,":[326],"gradient-based":[331,341],"we":[334],"implement":[335],"both":[336,361],"linear":[338],"nonlinear":[340],"methods":[343],"reconstruct":[345],"demonstrate":[350],"advantages":[353],"drawbacks.":[355],"governing":[357,483],"equations":[359,484],"formulated":[369],"integral":[375],"differential":[378],"equations.":[379,505],"proposed":[381],"verified":[387],"2D":[391],"3D":[393],"MRI-based":[394],"models.":[396],"It":[397],"is,":[398],"thus,":[399],"remarked":[400],"prepared":[403],"depicts":[405],"solid":[407],"outcome":[416],"chance":[418],"survival,":[420],"continuously":[422],"providing":[423,446],"updates":[426],"behaviour.":[430],"last":[432],"chapter":[433,455],"moves":[437],"one":[438],"step":[439],"further":[440],"implementing":[442],"quantum":[443],"electrodynamics":[444],"more":[447,475],"solutions":[449],"theory.":[452],"Though":[453],"directly":[458],"target":[459],"problem,":[462],"suggests":[464],"quantum-mechanical":[466],"reformulation":[467],"existing":[470],"theory":[472],"1)":[474],"solve":[477],"classical":[479],"problems":[480],"including":[481],"EMT,":[486],"2)":[488],"cover":[489],"wider":[491],"range":[492],"problems,":[494],"which":[497],"fundamentally":[500],"describable":[501],"Maxwell":[504]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
