{"id":"https://openalex.org/W2156356990","doi":"https://doi.org/10.1109/isbi.2004.1398517","title":"Multiresolution hierarchical blind recovery of biochemical markers of brain cancer in MRSI","display_name":"Multiresolution hierarchical blind recovery of biochemical markers of brain cancer in MRSI","publication_year":2005,"publication_date":"2005-04-12","ids":{"openalex":"https://openalex.org/W2156356990","doi":"https://doi.org/10.1109/isbi.2004.1398517","mag":"2156356990"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2004.1398517","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2004.1398517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821)","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/A5102142571","display_name":"Shuyan Du","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shuyan Du","raw_affiliation_strings":["Department of Biomedical Engineering, Columbia University, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042749874","display_name":"Paul Sajda","orcid":"https://orcid.org/0000-0002-9738-1342"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"P. Sajda","raw_affiliation_strings":["Department of Biomedical Engineering, Columbia University, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063655069","display_name":"Xiangling Mao","orcid":"https://orcid.org/0000-0003-2274-8282"},"institutions":[{"id":"https://openalex.org/I98704320","display_name":"Icahn School of Medicine at Mount Sinai","ror":"https://ror.org/04a9tmd77","country_code":"US","type":"education","lineage":["https://openalex.org/I1320796813","https://openalex.org/I98704320"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiangling Mao","raw_affiliation_strings":["Department of Radiology, Mount Sinai School of Medicine, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Mount Sinai School of Medicine, New York, NY, USA","institution_ids":["https://openalex.org/I98704320"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029763155","display_name":"Dikoma C. Shungu","orcid":"https://orcid.org/0000-0001-9452-2245"},"institutions":[{"id":"https://openalex.org/I98704320","display_name":"Icahn School of Medicine at Mount Sinai","ror":"https://ror.org/04a9tmd77","country_code":"US","type":"education","lineage":["https://openalex.org/I1320796813","https://openalex.org/I98704320"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D. Shungu","raw_affiliation_strings":["Department of Radiology, Mount Sinai School of Medicine, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Mount Sinai School of Medicine, New York, NY, USA","institution_ids":["https://openalex.org/I98704320"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102142571"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":0.3179,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61268368,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"233","last_page":"236"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12748","display_name":"Molecular spectroscopy and chirality","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9927999973297119,"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/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.8205983638763428},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.8028768301010132},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6247289180755615},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5817140936851501},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.557361364364624},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.53943932056427},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5120916366577148},{"id":"https://openalex.org/keywords/magnetic-resonance-spectroscopic-imaging","display_name":"Magnetic resonance spectroscopic imaging","score":0.5022561550140381},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4862629175186157},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.4198182225227356},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3800235092639923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.365500271320343},{"id":"https://openalex.org/keywords/biological-system","display_name":"Biological system","score":0.32514482736587524},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.2709558606147766},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26672160625457764},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.2611656188964844},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.19170674681663513},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.17925426363945007},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.13831371068954468},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.08545136451721191},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.08352819085121155}],"concepts":[{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.8205983638763428},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.8028768301010132},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6247289180755615},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5817140936851501},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.557361364364624},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.53943932056427},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5120916366577148},{"id":"https://openalex.org/C96781048","wikidata":"https://www.wikidata.org/wiki/Q6731601","display_name":"Magnetic resonance spectroscopic imaging","level":3,"score":0.5022561550140381},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4862629175186157},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.4198182225227356},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3800235092639923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.365500271320343},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.32514482736587524},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.2709558606147766},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26672160625457764},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.2611656188964844},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.19170674681663513},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.17925426363945007},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.13831371068954468},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.08545136451721191},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.08352819085121155},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2004.1398517","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2004.1398517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.7099999785423279,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W52608200","https://openalex.org/W1686946872","https://openalex.org/W1902027874","https://openalex.org/W2061692347","https://openalex.org/W2084681095","https://openalex.org/W2135029798","https://openalex.org/W2785356762","https://openalex.org/W2979454998","https://openalex.org/W4285719527","https://openalex.org/W6602128611","https://openalex.org/W6637108112","https://openalex.org/W6680012447","https://openalex.org/W6747634744"],"related_works":["https://openalex.org/W4308269461","https://openalex.org/W4281395053","https://openalex.org/W2020769413","https://openalex.org/W2766940489","https://openalex.org/W2127243424","https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2792706544","https://openalex.org/W1568451138"],"abstract_inverted_index":{"We":[0,45,91],"present":[1],"a":[2,37,85],"multi-resolution":[3],"hierarchical":[4],"application":[5],"of":[6,30,42,64,81,108],"the":[7,61,93,126],"constrained":[8],"non-negative":[9,31],"matrix":[10,32],"factorization":[11,33],"(cNMF)":[12],"algorithm":[13,127],"for":[14,77,110,135],"blindly":[15],"recovering":[16],"constituent":[17],"source":[18],"spectra":[19,72,79],"in":[20,60,137],"magnetic":[21],"resonance":[22],"spectroscopic":[23],"imaging":[24],"(MRSI).":[25],"cNMF":[26,47],"is":[27,132],"an":[28],"extension":[29],"(NMF)":[34],"that":[35,88],"includes":[36],"positivity":[38],"constraint":[39],"on":[40,96],"amplitudes":[41],"recovered":[43],"spectra.":[44],"apply":[46],"hierarchically,":[48],"with":[49],"spectral":[50],"recovery":[51,107],"and":[52,117],"subspace":[53],"reduction":[54],"constraining":[55],"which":[56,73],"observations":[57],"are":[58,74],"used":[59],"next":[62],"level":[63],"processing.":[65],"The":[66,104,121],"decomposition":[67,94],"model":[68],"recovers":[69],"physically":[70],"meaningful":[71],"highly":[75,118],"tissue-specific,":[76],"example":[78],"indicative":[80],"tumor":[82],"proliferation,":[83],"given":[84],"processing":[86],"hierarchy":[87,123],"proceeds":[89],"coarse-to-fine.":[90],"demonstrate":[92],"procedure":[95],"/sup":[97],"1/H":[98],"long":[99],"TE":[100],"brain":[101,112],"MRS":[102],"data.":[103],"results":[105],"show":[106],"markers":[109],"normal":[111],"tissue,":[113],"low":[114],"proliferative":[115,119],"tissue":[116],"tissue.":[120],"coarse-to-fine":[122],"also":[124],"makes":[125],"computationally":[128],"efficient,":[129],"thus":[130],"it":[131],"potentially":[133],"well-suited":[134],"use":[136],"diagnostic":[138],"work-up.":[139]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
