{"id":"https://openalex.org/W2959161917","doi":"https://doi.org/10.1109/isbi.2019.8759558","title":"DMR-CNN: A CNN Tailored For DMR Scans With Applications To PD Classification","display_name":"DMR-CNN: A CNN Tailored For DMR Scans With Applications To PD Classification","publication_year":2019,"publication_date":"2019-04-01","ids":{"openalex":"https://openalex.org/W2959161917","doi":"https://doi.org/10.1109/isbi.2019.8759558","mag":"2959161917"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2019.8759558","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2019.8759558","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)","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/A5101120703","display_name":"Monami Banerjee","orcid":null},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Monami Banerjee","raw_affiliation_strings":["University of Florida, Gainesville, FL, USA"],"affiliations":[{"raw_affiliation_string":"University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025100345","display_name":"Rudrasis Chakraborty","orcid":"https://orcid.org/0000-0002-0448-911X"},"institutions":[{"id":"https://openalex.org/I1297971548","display_name":"International Computer Science Institute","ror":"https://ror.org/01ewh7m12","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1297971548"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rudrasis Chakraborty","raw_affiliation_strings":["University of California ICSI, Berkeley"],"affiliations":[{"raw_affiliation_string":"University of California ICSI, Berkeley","institution_ids":["https://openalex.org/I1297971548"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028369148","display_name":"Derek B. Archer","orcid":"https://orcid.org/0000-0001-8638-0785"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Derek Archer","raw_affiliation_strings":["University of Florida, Gainesville, FL, USA"],"affiliations":[{"raw_affiliation_string":"University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019592840","display_name":"David E. Vaillancourt","orcid":"https://orcid.org/0000-0002-5663-6476"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Vaillancourt","raw_affiliation_strings":["University of Florida, Gainesville, FL, USA"],"affiliations":[{"raw_affiliation_string":"University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016378470","display_name":"Baba C. Vemuri","orcid":"https://orcid.org/0000-0002-1400-5844"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Baba C. Vemuri","raw_affiliation_strings":["University of Florida, Gainesville, FL, USA"],"affiliations":[{"raw_affiliation_string":"University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101120703"],"corresponding_institution_ids":["https://openalex.org/I33213144"],"apc_list":null,"apc_paid":null,"fwci":1.3547,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.81177634,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":1.0,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":1.0,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9991999864578247,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.7125889658927917},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.675125241279602},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6729415059089661},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.640040397644043},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.579625129699707},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.4989638328552246},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.4599321186542511},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.42285627126693726},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2444612681865692},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.08613312244415283}],"concepts":[{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.7125889658927917},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.675125241279602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6729415059089661},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.640040397644043},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.579625129699707},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.4989638328552246},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4599321186542511},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.42285627126693726},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2444612681865692},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.08613312244415283},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2019.8759558","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2019.8759558","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1964802316","https://openalex.org/W2044904021","https://openalex.org/W2087640086","https://openalex.org/W2112796928","https://openalex.org/W2321536610","https://openalex.org/W2785397276","https://openalex.org/W2804126069","https://openalex.org/W2963564809","https://openalex.org/W3118608800","https://openalex.org/W4293362962","https://openalex.org/W6743757654","https://openalex.org/W6748579715","https://openalex.org/W6751831310","https://openalex.org/W6769516661","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W1989570877","https://openalex.org/W1966577812","https://openalex.org/W2953252165","https://openalex.org/W2563901864","https://openalex.org/W3168009835","https://openalex.org/W1998589401","https://openalex.org/W2964287305","https://openalex.org/W1653893795","https://openalex.org/W1979518822","https://openalex.org/W1976920294"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"are":[3],"ubiquitous":[4],"in":[5,21,66,113,116],"Machine":[6],"Learning":[7],"applications":[8],"for":[9,77],"solving":[10],"a":[11,98,109,121,138,187],"variety":[12],"of":[13,28,47,57,79,89,111,140,168,189],"problems.":[14],"They":[15],"however":[16],"can":[17],"not":[18],"be":[19],"used":[20],"their":[22],"native":[23],"form":[24],"when":[25],"the":[26,29,37,39,43,45,90,93,157,161],"domain":[27],"data":[30],"is":[31,95],"commonly":[32],"encountered":[33],"manifolds":[34],"such":[35],"as":[36,97],"sphere,":[38],"special":[40],"orthogonal":[41],"group,":[42],"Grassmannian,":[44],"manifold":[46],"symmetric":[48],"positive":[49],"definite":[50],"matrices":[51],"and":[52,149,194],"others.":[53],"Most":[54],"recently,":[55],"generalization":[56],"CNNs":[58],"to":[59,145,155,170,181],"Riemannian":[60],"homogeneous":[61],"spaces":[62],"have":[63,120],"been":[64],"reported":[65],"literature.":[67],"In":[68,86],"this":[69,143],"work,":[70],"we":[71,119],"propose":[72],"an":[73,178],"end-to-end":[74],"CNN":[75,153],"architecture":[76],"classification":[78],"diffusion":[80,103],"MRI":[81],"(dMRI)":[82],"signals,":[83],"dubbed":[84],"dMR-CNN.":[85],"each":[87,102,117],"voxel":[88],"dMRI":[91,183],"scan,":[92],"signal":[94],"acquired":[96,185],"real":[99],"number":[100],"along":[101],"sensitizing":[104],"magnetic":[105],"field":[106],"direction":[107],"over":[108],"hemisphere":[110],"directions":[112],"3D.":[114],"Hence,":[115],"voxel,":[118],"function":[122],"f":[123],":":[124],"S":[125],"<sup":[126],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[127,132],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[128],"\u00d7":[129],"P":[130],"<sub":[131],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[133],"\u2192":[134],"R.":[135],"We":[136,176],"formulate":[137],"definition":[139],"correlation":[141],"on":[142],"space":[144],"extract":[146,171],"intra-voxel":[147,162],"features":[148],"then":[150],"use":[151],"standard":[152],"model":[154],"capture":[156],"spatial":[158],"interactions":[159],"between":[160],"features.":[163,175],"Our":[164],"proposed":[165],"framework":[166],"comprises":[167],"architectures":[169],"these":[172],"intraand":[173],"intervoxel":[174],"present":[177],"experimental":[179],"setup":[180],"classify":[182],"scans":[184],"from":[186],"cohort":[188],"44":[190],"Parkinson":[191],"Disease":[192],"patients":[193],"50":[195],"control/normal":[196],"subjects.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
