{"id":"https://openalex.org/W7150774429","doi":"https://doi.org/10.48550/arxiv.2604.03150","title":"HyperFitS -- Hypernetwork Fitting Spectra for metabolic quantification of ${}^1$H MR spectroscopic imaging","display_name":"HyperFitS -- Hypernetwork Fitting Spectra for metabolic quantification of ${}^1$H MR spectroscopic imaging","publication_year":2026,"publication_date":"2026-04-03","ids":{"openalex":"https://openalex.org/W7150774429","doi":"https://doi.org/10.48550/arxiv.2604.03150"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.03150","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.03150","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.03150","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133024274","display_name":"Paul J. Weiser","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weiser, Paul J.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012984691","display_name":"G\u00fclnur Ungan","orcid":"https://orcid.org/0000-0002-5436-4665"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ungan, Gulnur","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011401253","display_name":"Amirmohammad Shamaei","orcid":"https://orcid.org/0000-0001-8342-3284"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shamaei, Amirmohammad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060814361","display_name":"Georg Langs","orcid":"https://orcid.org/0000-0002-5536-6873"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Langs, Georg","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023652216","display_name":"Wolfgang Bogner","orcid":"https://orcid.org/0000-0002-0130-3463"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bogner, Wolfgang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133023319","display_name":"Malte Hoffmann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hoffmann, Malte","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074341922","display_name":"Antoine Klauser","orcid":"https://orcid.org/0000-0003-3019-9914"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Klauser, Antoine","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5056477611","display_name":"Ovidiu C. Andronesi","orcid":"https://orcid.org/0000-0002-7412-0641"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Andronesi, Ovidiu C.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9825000166893005,"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":0.9825000166893005,"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/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.006200000178068876,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.00139999995008111,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5848000049591064},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5221999883651733},{"id":"https://openalex.org/keywords/parametrization","display_name":"Parametrization (atmospheric modeling)","score":0.5047000050544739},{"id":"https://openalex.org/keywords/metabolite","display_name":"Metabolite","score":0.46939998865127563},{"id":"https://openalex.org/keywords/magnetic-resonance-spectroscopic-imaging","display_name":"Magnetic resonance spectroscopic imaging","score":0.4171999990940094},{"id":"https://openalex.org/keywords/spectral-line","display_name":"Spectral line","score":0.41690000891685486},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.3467999994754791},{"id":"https://openalex.org/keywords/isotropy","display_name":"Isotropy","score":0.3463999927043915}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5848000049591064},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5680000185966492},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5221999883651733},{"id":"https://openalex.org/C202887219","wikidata":"https://www.wikidata.org/wiki/Q3895221","display_name":"Parametrization (atmospheric modeling)","level":3,"score":0.5047000050544739},{"id":"https://openalex.org/C2777477808","wikidata":"https://www.wikidata.org/wiki/Q407595","display_name":"Metabolite","level":2,"score":0.46939998865127563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44040000438690186},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.4302999973297119},{"id":"https://openalex.org/C96781048","wikidata":"https://www.wikidata.org/wiki/Q6731601","display_name":"Magnetic resonance spectroscopic imaging","level":3,"score":0.4171999990940094},{"id":"https://openalex.org/C4839761","wikidata":"https://www.wikidata.org/wiki/Q212111","display_name":"Spectral line","level":2,"score":0.41690000891685486},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38420000672340393},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.36419999599456787},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3467999994754791},{"id":"https://openalex.org/C184050105","wikidata":"https://www.wikidata.org/wiki/Q273163","display_name":"Isotropy","level":2,"score":0.3463999927043915},{"id":"https://openalex.org/C2988005100","wikidata":"https://www.wikidata.org/wiki/Q1979695","display_name":"Proton magnetic resonance","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34220001101493835},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.3361999988555908},{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.3255000114440918},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.31029999256134033},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2962999939918518},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C101810790","wikidata":"https://www.wikidata.org/wiki/Q2263094","display_name":"Metabolic network","level":2,"score":0.29010000824928284},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C3019809220","wikidata":"https://www.wikidata.org/wiki/Q904043","display_name":"Echo time","level":3,"score":0.2770000100135803},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.2734000086784363},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C2984127161","wikidata":"https://www.wikidata.org/wiki/Q969316","display_name":"Neural activity","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.03150","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.03150","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.03150","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.03150","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Purpose:":[0],"Proton":[1],"magnetic":[2],"resonance":[3],"spectroscopic":[4],"imaging":[5],"($^1$H":[6],"MRSI)":[7],"enables":[8,203],"the":[9,25,142,158],"mapping":[10],"of":[11,91,100,111,160,207],"whole-brain":[12,45,81],"metabolites":[13],"concentrations":[14],"in-vivo.":[15],"However,":[16,53],"a":[17,50,72,88,138,190,204],"long-standing":[18],"problem":[19],"for":[20,33,74,77],"its":[21],"clinical":[22],"applicability":[23],"is":[24],"metabolic":[26,46,164],"quantification,":[27,165],"which":[28,166],"can":[29,167,210],"require":[30,61],"extensive":[31],"time":[32],"spectral":[34,75,199],"fitting.":[35,133],"Recently,":[36],"deep":[37,196],"learning":[38,197],"methods":[39],"have":[40],"been":[41],"able":[42],"to":[43,63,87,130,172,189,194,212],"provide":[44],"quantification":[47,79],"in":[48,80],"only":[49],"few":[51,191],"seconds.":[52,192],"neural":[54],"network":[55],"implementations":[56],"often":[57],"lack":[58],"configurability":[59,208],"and":[60,94,106,116,121,128,144,209,219],"retraining":[62],"change":[64],"predefined":[65],"parameter":[66],"settings.":[67],"Methods:":[68],"We":[69],"introduce":[70],"HyperFitS,":[71],"hypernetwork":[73],"fitting":[76,150,200],"metabolite":[78],"$^1$H":[82],"MRSI":[83,123],"that":[84],"flexibly":[85],"adapts":[86],"broad":[89],"range":[90,206],"baseline":[92,161],"corrections":[93],"water":[95],"suppression":[96],"factors.":[97],"Metabolite":[98],"maps":[99,136],"human":[101],"subjects":[102],"acquired":[103,215],"at":[104],"3T":[105],"7T":[107],"with":[108,126,147,179,216],"isotropic":[109],"resolutions":[110],"10":[112],"mm,":[113],"3.4":[114],"mm":[115,118],"2":[117],"by":[119,152,170],"water-suppressed":[120],"water-unsuppressed":[122],"were":[124],"quantified":[125],"HyperFitS":[127,175,202],"compared":[129],"conventional":[131,181],"LCModel":[132],"Results:":[134],"Metabolic":[135],"show":[137],"substantial":[139],"agreement":[140,178],"between":[141],"new":[143],"gold-standard":[145],"methods,":[146,182,201],"significantly":[148],"faster":[149],"times":[151,186],"HyperFitS.":[153],"Quantitative":[154],"results":[155,169],"further":[156],"highlight":[157],"impact":[159],"parametrization":[162],"on":[163],"alter":[168],"up":[171],"30%.":[173],"Conclusion:":[174],"shows":[176],"strong":[177],"state-of-the-art":[180],"while":[183],"reducing":[184],"processing":[185],"from":[187],"hours":[188],"Compared":[193],"prior":[195],"based":[198],"wide":[205],"adapt":[211],"data":[213],"quality":[214],"multiple":[217],"protocols":[218],"field":[220],"strengths":[221],"without":[222],"retraining.":[223]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-07T00:00:00"}