{"id":"https://openalex.org/W2068776911","doi":"https://doi.org/10.1117/1.2731782","title":"Partial volume and distribution estimation from multispectral images using continuous representations","display_name":"Partial volume and distribution estimation from multispectral images using continuous representations","publication_year":2007,"publication_date":"2007-10-01","ids":{"openalex":"https://openalex.org/W2068776911","doi":"https://doi.org/10.1117/1.2731782","mag":"2068776911"},"language":"en","primary_location":{"id":"doi:10.1117/1.2731782","is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.2731782","pdf_url":null,"source":{"id":"https://openalex.org/S158511090","display_name":"Journal of Electronic Imaging","issn_l":"1017-9909","issn":["1017-9909","1560-229X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electronic Imaging","raw_type":"journal-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/A5058761102","display_name":"Hamid Soltanian\u2010Zadeh","orcid":"https://orcid.org/0000-0002-7302-6856"},"institutions":[{"id":"https://openalex.org/I154057602","display_name":"Henry Ford Health System","ror":"https://ror.org/02kwnkm68","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I154057602"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hamid Soltanian-Zadeh","raw_affiliation_strings":["Henry Ford Health System (United States)","Henry Ford Health System, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henry Ford Health System (United States)","institution_ids":["https://openalex.org/I154057602"]},{"raw_affiliation_string":"Henry Ford Health System, United States","institution_ids":["https://openalex.org/I154057602"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5058761102"],"corresponding_institution_ids":["https://openalex.org/I154057602"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12024485,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"4","first_page":"043001","last_page":"043001"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9955999851226807,"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/T10862","display_name":"AI in cancer detection","score":0.995199978351593,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.8389603495597839},{"id":"https://openalex.org/keywords/spline","display_name":"Spline (mechanical)","score":0.6504000425338745},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5648009181022644},{"id":"https://openalex.org/keywords/standard-deviation","display_name":"Standard deviation","score":0.5379773378372192},{"id":"https://openalex.org/keywords/b-spline","display_name":"B-spline","score":0.5357778072357178},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.48258841037750244},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4754576086997986},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.466011106967926},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.38662683963775635},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.35281237959861755},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2517678737640381},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23702532052993774},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.12488088011741638}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8389603495597839},{"id":"https://openalex.org/C10390562","wikidata":"https://www.wikidata.org/wiki/Q581809","display_name":"Spline (mechanical)","level":2,"score":0.6504000425338745},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5648009181022644},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.5379773378372192},{"id":"https://openalex.org/C15945459","wikidata":"https://www.wikidata.org/wiki/Q2083109","display_name":"B-spline","level":2,"score":0.5357778072357178},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.48258841037750244},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4754576086997986},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.466011106967926},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38662683963775635},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.35281237959861755},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2517678737640381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23702532052993774},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.12488088011741638},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/1.2731782","is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.2731782","pdf_url":null,"source":{"id":"https://openalex.org/S158511090","display_name":"Journal of Electronic Imaging","issn_l":"1017-9909","issn":["1017-9909","1560-229X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electronic Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309659","display_name":"Henry Ford Health System","ror":"https://ror.org/02kwnkm68"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1594581940","https://openalex.org/W1605096437","https://openalex.org/W1967635500","https://openalex.org/W1969292798","https://openalex.org/W2003410902","https://openalex.org/W2020717731","https://openalex.org/W2031675154","https://openalex.org/W2038896048","https://openalex.org/W2042304314","https://openalex.org/W2064819030","https://openalex.org/W2065628492","https://openalex.org/W2066652768","https://openalex.org/W2070365781","https://openalex.org/W2073061978","https://openalex.org/W2098397361","https://openalex.org/W2098982273","https://openalex.org/W2108543930","https://openalex.org/W2115012068","https://openalex.org/W2119231080","https://openalex.org/W2119807014","https://openalex.org/W2119955085","https://openalex.org/W2125523738","https://openalex.org/W2132051037","https://openalex.org/W2134215223","https://openalex.org/W2136573752","https://openalex.org/W2137206388","https://openalex.org/W2139012366","https://openalex.org/W2141666257","https://openalex.org/W2145860001","https://openalex.org/W2150664451","https://openalex.org/W2151050383","https://openalex.org/W2151952539","https://openalex.org/W2161557710","https://openalex.org/W2162297789","https://openalex.org/W2168536273","https://openalex.org/W2171765626","https://openalex.org/W3016413756"],"related_works":["https://openalex.org/W4318664220","https://openalex.org/W2771047279","https://openalex.org/W4388409104","https://openalex.org/W2131662362","https://openalex.org/W2052425187","https://openalex.org/W2766141905","https://openalex.org/W3153287478","https://openalex.org/W3084529718","https://openalex.org/W1566260961","https://openalex.org/W2487825112"],"abstract_inverted_index":{"When":[0],"estimating":[1],"partial":[2],"volume":[3],"effects":[4],"in":[5],"the":[6,14,48,53,57,61,77,93,96,103,106,119,152],"presence":[7],"of":[8,47,82,92,118,134],"noise,":[9],"using":[10],"neighboring":[11,32,54],"information":[12,33,55],"improves":[13],"estimation.":[15],"The":[16],"optimal":[17],"linear":[18],"transformation":[19],"(OLT)":[20],"is":[21,36,100],"an":[22,131],"unbiased":[23],"minimum":[24],"variance":[25],"estimator.":[26],"However,":[27,125],"it":[28],"does":[29],"not":[30],"use":[31,64],"and":[34,43,66,72,76,146],"thus":[35],"sensitive":[37],"to":[38,50,87,123,140],"noise.":[39],"We":[40],"employ":[41],"polynomial":[42],"B-spline":[44,113,126,136],"continuous":[45],"representations":[46],"data":[49],"mathematically":[51],"incorporate":[52],"into":[56],"OLT.":[58,153],"To":[59],"evaluate":[60],"method,":[62],"we":[63],"synthetic":[65],"actual":[67],"images":[68],"generated":[69],"by":[70],"simulation":[71],"acquired":[73],"from":[74],"phantoms":[75],"human":[78],"brain.":[79],"Standard":[80],"deviations":[81],"new":[83],"estimators":[84,114,127,137],"are":[85,138],"up":[86,139],"60%":[88],"less":[89],"than":[90,144,151],"that":[91],"OLT":[94],"when":[95],"signal-to-noise":[97],"ratio":[98],"(SNR)":[99],"25.":[101],"As":[102],"SNR":[104],"decreases,":[105],"proposed":[107],"method":[108],"demonstrates":[109],"more":[110],"improvements.":[111],"Overall,":[112],"provide":[115],"larger":[116],"estimations":[117],"standard":[120],"deviation":[121],"compared":[122],"polynomials.":[124],"outperform":[128],"polynomials,":[129],"providing":[130],"arbitrary":[132],"degree":[133],"continuity.":[135],"10":[141,148],"times":[142,149],"faster":[143],"polynomials":[145],"about":[147],"slower":[150]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
