{"id":"https://openalex.org/W2532970495","doi":"https://doi.org/10.1109/aipr.2008.4906453","title":"Non-Gaussian methods in biomedical imaging","display_name":"Non-Gaussian methods in biomedical imaging","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W2532970495","doi":"https://doi.org/10.1109/aipr.2008.4906453","mag":"2532970495"},"language":"en","primary_location":{"id":"doi:10.1109/aipr.2008.4906453","doi":"https://doi.org/10.1109/aipr.2008.4906453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr.2008.4906453","pdf_url":null,"source":{"id":"https://openalex.org/S4393918249","display_name":"IEEE Applied Imagery Pattern Recognition Workshop","issn_l":"2164-2516","issn":["2164-2516"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 37th IEEE Applied Imagery Pattern Recognition Workshop","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5024456828","display_name":"Rami Mangoubi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1343143571","display_name":"Draper Laboratory","ror":"https://ror.org/04378d909","country_code":"US","type":"funder","lineage":["https://openalex.org/I1343143571"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rami Mangoubi","raw_affiliation_strings":["C. S. Draper Laboratories, Inc., Cambridge, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"C. S. Draper Laboratories, Inc., Cambridge, MA, USA","institution_ids":["https://openalex.org/I1343143571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112033840","display_name":"Mukund N. Desai","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1343143571","display_name":"Draper Laboratory","ror":"https://ror.org/04378d909","country_code":"US","type":"funder","lineage":["https://openalex.org/I1343143571"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mukund Desai","raw_affiliation_strings":["C. S. Draper Laboratories, Inc., Cambridge, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"C. S. Draper Laboratories, Inc., Cambridge, MA, USA","institution_ids":["https://openalex.org/I1343143571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076887346","display_name":"Paul J. Sammak","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]},{"id":"https://openalex.org/I4210097282","display_name":"Magee-Womens Research Institute","ror":"https://ror.org/00rnw4e09","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210097282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paul Sammak","raw_affiliation_strings":["Magee-Womens Research Institute, University of Pittsburgh, Pittsburgh, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Magee-Womens Research Institute, University of Pittsburgh, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I170201317","https://openalex.org/I4210097282"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.267,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.53741026,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.5922999978065491,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.5922999978065491,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.2078000009059906,"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":0.036400001496076584,"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-gaussian-statistics","display_name":"non-Gaussian statistics","score":0.8309999704360962},{"id":"https://openalex.org/keywords/laplace-distribution","display_name":"Laplace distribution","score":0.7120000123977661},{"id":"https://openalex.org/keywords/generalized-gaussian-distribution","display_name":"generalized Gaussian distribution","score":0.7910000085830688},{"id":"https://openalex.org/keywords/false-alarm-rate","display_name":"false alarm rate","score":0.5419999957084656},{"id":"https://openalex.org/keywords/image-classification","display_name":"image classification","score":0.5509999990463257},{"id":"https://openalex.org/keywords/multiple-images","display_name":"multiple images","score":0.5860000252723694},{"id":"https://openalex.org/keywords/fmri","display_name":"functional MRI","score":0.9800000190734863},{"id":"https://openalex.org/keywords/stem-cell-classification","display_name":"stem cell classification","score":0.9139999747276306},{"id":"https://openalex.org/keywords/medical-image-analysis","display_name":"medical image analysis","score":0.5640000104904175}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.7901157736778259},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6067519783973694},{"id":"https://openalex.org/C97937538","wikidata":"https://www.wikidata.org/wiki/Q199691","display_name":"Laplace transform","level":2,"score":0.5643507838249207},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.5597119331359863},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.552802324295044},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.4839935302734375},{"id":"https://openalex.org/C51267290","wikidata":"https://www.wikidata.org/wiki/Q5527848","display_name":"Gaussian random field","level":4,"score":0.47702571749687195},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4656107723712921},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.4624692499637604},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4577646553516388},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40106087923049927},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39345648884773254},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.3607698678970337},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34074652194976807},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3108106255531311},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17556661367416382},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12488138675689697},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aipr.2008.4906453","doi":"https://doi.org/10.1109/aipr.2008.4906453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr.2008.4906453","pdf_url":null,"source":{"id":"https://openalex.org/S4393918249","display_name":"IEEE Applied Imagery Pattern Recognition Workshop","issn_l":"2164-2516","issn":["2164-2516"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 37th IEEE Applied Imagery Pattern Recognition Workshop","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W70821729","https://openalex.org/W181283568","https://openalex.org/W202677556","https://openalex.org/W633766847","https://openalex.org/W1578953027","https://openalex.org/W1586623350","https://openalex.org/W1968590503","https://openalex.org/W1983913844","https://openalex.org/W2030398291","https://openalex.org/W2052199757","https://openalex.org/W2097106406","https://openalex.org/W2099074763","https://openalex.org/W2127327508","https://openalex.org/W2133772052","https://openalex.org/W2142893731","https://openalex.org/W2150690737","https://openalex.org/W2163534628","https://openalex.org/W2743279517","https://openalex.org/W4298032380"],"related_works":["https://openalex.org/W2998144608","https://openalex.org/W6922633121","https://openalex.org/W2106420113","https://openalex.org/W7101126890","https://openalex.org/W2161485731","https://openalex.org/W1980864340","https://openalex.org/W2105505221","https://openalex.org/W2100164534","https://openalex.org/W2353286992","https://openalex.org/W2114442655"],"abstract_inverted_index":{"Most":[0],"statistical":[1],"models":[2,85],"for":[3,26,60],"applications":[4,89],"rely":[5],"on":[6],"the":[7,15,28,38,47,50,57,71],"Gaussian":[8,29,58,73],"assumption.":[9],"Yet,":[10],"in":[11,35,46,96],"many":[12],"realistic":[13],"situations,":[14],"underlying":[16],"variation":[17],"or":[18],"uncertainty":[19],"is":[20,40],"essentially":[21],"non-Gaussian.":[22],"In":[23,54],"detection":[24],"problems,":[25,56],"instance,":[27],"assumption":[30],"leads":[31],"to":[32,88],"false":[33],"alarms":[34],"cases":[36],"where":[37],"tail":[39],"a":[41],"fatter":[42],"one,":[43],"such":[44,69,84],"as":[45,70,86],"case":[48],"of":[49,83],"Laplace":[51],"density":[52,74],"function.":[53],"classification":[55],"model":[59],"variability":[61],"may":[62],"be":[63],"too":[64],"restrictive,":[65],"and":[66,93,103],"other":[67],"models,":[68],"Generalized":[72],"function,":[75],"are":[76],"more":[77],"appropriate.":[78],"We":[79],"will":[80],"present":[81],"examples":[82],"applied":[87],"with":[90],"multiple":[91],"images,":[92],"show":[94],"performance":[95],"two":[97],"applications:":[98],"functional":[99],"magnetic":[100],"resonance":[101],"imaging,":[102],"stem":[104],"cell":[105],"classification.":[106]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-10-28T00:00:00"}
