{"id":"https://openalex.org/W3013416319","doi":"https://doi.org/10.1109/ieeeconf44664.2019.9048805","title":"Modeling Variability in Brain Architecture with Deep Feature Learning","display_name":"Modeling Variability in Brain Architecture with Deep Feature Learning","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3013416319","doi":"https://doi.org/10.1109/ieeeconf44664.2019.9048805","mag":"3013416319"},"language":"en","primary_location":{"id":"doi:10.1109/ieeeconf44664.2019.9048805","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf44664.2019.9048805","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 53rd Asilomar Conference on Signals, Systems, and Computers","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/A5014018371","display_name":"Aishwarya Balwani","orcid":"https://orcid.org/0000-0002-9234-1632"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Aishwarya H. Balwani","raw_affiliation_strings":["Georgia Institute of Technology,School of Electrical and Computer Engineering,Atlanta,USA","School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,School of Electrical and Computer Engineering,Atlanta,USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064062853","display_name":"Eva L. Dyer","orcid":"https://orcid.org/0000-0002-6962-524X"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]},{"id":"https://openalex.org/I2802612298","display_name":"The Wallace H. Coulter Department of Biomedical Engineering","ror":"https://ror.org/02j15s898","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444","https://openalex.org/I150468666","https://openalex.org/I2802612298"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eva L. Dyer","raw_affiliation_strings":["Georgia Institute of Technology,Coulter Department of Biomedical Engineering,Atlanta,USA","Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, USA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,Coulter Department of Biomedical Engineering,Atlanta,USA","institution_ids":["https://openalex.org/I2802612298","https://openalex.org/I130701444"]},{"raw_affiliation_string":"Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, USA","institution_ids":["https://openalex.org/I2802612298","https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5014018371"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":0.28,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68129142,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1186","last_page":"1191"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.982200026512146,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.982200026512146,"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/T10320","display_name":"Neural Networks and Applications","score":0.9810000061988831,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9787999987602234,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7276244163513184},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.6272937059402466},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5969752073287964},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5963847041130066},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5283048152923584},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3513343334197998},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09265118837356567}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7276244163513184},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.6272937059402466},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5969752073287964},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5963847041130066},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5283048152923584},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3513343334197998},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09265118837356567},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieeeconf44664.2019.9048805","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf44664.2019.9048805","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 53rd Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W189596042","https://openalex.org/W1849277567","https://openalex.org/W1913338476","https://openalex.org/W2064741852","https://openalex.org/W2083099567","https://openalex.org/W2122922389","https://openalex.org/W2155541015","https://openalex.org/W2156509565","https://openalex.org/W2161381512","https://openalex.org/W2337567566","https://openalex.org/W2592483666","https://openalex.org/W2603597171","https://openalex.org/W2616728375","https://openalex.org/W2726367589","https://openalex.org/W2794677645","https://openalex.org/W2875369846","https://openalex.org/W2921596675","https://openalex.org/W2922111081","https://openalex.org/W2963542991","https://openalex.org/W2987188183","https://openalex.org/W3100262678","https://openalex.org/W4294375521","https://openalex.org/W6607775107","https://openalex.org/W6629368666","https://openalex.org/W6639933941","https://openalex.org/W6682778277","https://openalex.org/W6687011383","https://openalex.org/W6749973366"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W2939353110","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756"],"abstract_inverted_index":{"The":[0],"brain":[1,52,93,118,147,164,176],"has":[2],"long":[3],"been":[4],"divided":[5],"into":[6,49],"distinct":[7],"areas":[8,44],"based":[9],"upon":[10],"its":[11],"local":[12],"microstructure,":[13],"or":[14],"patterned":[15],"composition":[16],"of":[17,51,62,71,117,130],"cells,":[18],"genes,":[19],"and":[20,28,73,102,114,123,165,182],"proteins.":[21],"While":[22],"this":[23,55,78],"taxonomy":[24],"is":[25,38,178],"incredibly":[26],"useful":[27],"provides":[29],"an":[30],"essential":[31],"roadmap":[32],"for":[33,127],"comparing":[34],"two":[35],"brains,":[36],"there":[37],"also":[39],"immense":[40],"anatomical":[41],"variability":[42],"within":[43,146],"that":[45,86,167,194],"must":[46],"be":[47,184],"incorporated":[48],"models":[50],"architecture.":[53,119],"In":[54],"work":[56],"we":[57,80],"leverage":[58],"the":[59,100,128,162,195],"expressive":[60],"power":[61],"deep":[63,133,169],"neural":[64,84,134,192],"networks":[65,135],"to":[66,107,142,153,180,186,199],"create":[67],"a":[68,82,104,111],"data-driven":[69],"model":[70,116,171],"intra-":[72],"inter-brain":[74],"area":[75],"variability.":[76],"To":[77],"end,":[79],"train":[81],"convolutional":[83],"network":[85,101,196],"learns":[87],"relevant":[88,189],"microstructural":[89],"features":[90,98,131],"directly":[91],"from":[92,99,132],"imagery.":[94],"We":[95,120,149],"then":[96],"extract":[97],"fit":[103],"simple":[105],"classifier":[106],"them,":[108],"thus":[109],"creating":[110],"simple,":[112],"robust,":[113],"interpretable":[115],"further":[121],"propose":[122],"show":[124],"preliminary":[125],"results":[126],"use":[129],"in":[136,161,191],"conjunction":[137],"with":[138],"unsupervised":[139],"learning":[140],"techniques":[141],"find":[143],"fine-grained":[144],"structure":[145],"areas.":[148],"apply":[150],"our":[151,168],"methods":[152],"micron-scale":[154],"X-ray":[155],"microtomography":[156],"images":[157],"spanning":[158],"multiple":[159],"regions":[160],"mouse":[163],"demonstrate":[166],"feature-based":[170],"can":[172,183],"reliably":[173],"discriminate":[174],"between":[175],"areas,":[177],"robust":[179],"noise,":[181],"used":[185],"reveal":[187],"anatomically":[188],"patterns":[190],"architecture":[193],"wasn't":[197],"trained":[198],"find.":[200]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
