{"id":"https://openalex.org/W2097823873","doi":"https://doi.org/10.1109/isbi.2013.6556609","title":"Thalamic parcellation from multi-modal data using random forest learning","display_name":"Thalamic parcellation from multi-modal data using random forest learning","publication_year":2013,"publication_date":"2013-04-01","ids":{"openalex":"https://openalex.org/W2097823873","doi":"https://doi.org/10.1109/isbi.2013.6556609","mag":"2097823873","pmid":"https://pubmed.ncbi.nlm.nih.gov/24145869"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2013.6556609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2013.6556609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE 10th International Symposium on Biomedical Imaging","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5011342579","display_name":"Joshua V. Stough","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Joshua V. Stough","raw_affiliation_strings":["Computer Science, Washington and Lee University, Lexington, VA USA"],"affiliations":[{"raw_affiliation_string":"Computer Science, Washington and Lee University, Lexington, VA USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040190038","display_name":"Chuyang Ye","orcid":"https://orcid.org/0000-0001-5839-1559"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chuyang Ye","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA","Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113605332","display_name":"Sarah H. Ying","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sarah H. Ying","raw_affiliation_strings":["Department of Radiology, Johns Hopkins University, Baltimore, MD, USA","Radiol., Johns Hopkins Univ., Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Radiol., Johns Hopkins Univ., Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066682675","display_name":"Jerry L. Prince","orcid":"https://orcid.org/0000-0002-6553-0876"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jerry L. Prince","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA","Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5011342579"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3241,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.80953482,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"852","last_page":"855"},"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9950000047683716,"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"}},{"id":"https://openalex.org/T12552","display_name":"Fetal and Pediatric Neurological Disorders","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/thalamus","display_name":"Thalamus","score":0.7159351110458374},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.6188449859619141},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5796153545379639},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5720848441123962},{"id":"https://openalex.org/keywords/diffusion-mri","display_name":"Diffusion MRI","score":0.5356269478797913},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5233518481254578},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4894045889377594},{"id":"https://openalex.org/keywords/fractional-anisotropy","display_name":"Fractional anisotropy","score":0.4701307713985443},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.4601910412311554},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.4113452434539795},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.34002578258514404},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.2582836151123047},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1295253038406372}],"concepts":[{"id":"https://openalex.org/C2779246727","wikidata":"https://www.wikidata.org/wiki/Q184215","display_name":"Thalamus","level":2,"score":0.7159351110458374},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.6188449859619141},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5796153545379639},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5720848441123962},{"id":"https://openalex.org/C149550507","wikidata":"https://www.wikidata.org/wiki/Q899360","display_name":"Diffusion MRI","level":3,"score":0.5356269478797913},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5233518481254578},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4894045889377594},{"id":"https://openalex.org/C89916169","wikidata":"https://www.wikidata.org/wiki/Q17014600","display_name":"Fractional anisotropy","level":4,"score":0.4701307713985443},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.4601910412311554},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.4113452434539795},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.34002578258514404},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2582836151123047},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1295253038406372},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/isbi.2013.6556609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2013.6556609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE 10th International Symposium on Biomedical Imaging","raw_type":"proceedings-article"},{"id":"pmid:24145869","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/24145869","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. IEEE International Symposium on Biomedical Imaging","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.724.2721","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.724.2721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://iacl.ece.jhu.edu//proceedings/iacl/2013/StouxISBI13-Thalmic_parcellation_using_random_forest.pdf","raw_type":"text"},{"id":"pmh:oai:europepmc.org:2791370","is_oa":false,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3799867","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1567026204","https://openalex.org/W1572808892","https://openalex.org/W1812516254","https://openalex.org/W1849904781","https://openalex.org/W1963781350","https://openalex.org/W1989033585","https://openalex.org/W1990264298","https://openalex.org/W1998299241","https://openalex.org/W2000439270","https://openalex.org/W2015512087","https://openalex.org/W2043538065","https://openalex.org/W2052993381","https://openalex.org/W2058224795","https://openalex.org/W2077300570","https://openalex.org/W2085578603","https://openalex.org/W2108961924","https://openalex.org/W2116136260","https://openalex.org/W2130751189","https://openalex.org/W2144331592","https://openalex.org/W2321710201","https://openalex.org/W2911964244","https://openalex.org/W4293171766","https://openalex.org/W6634084405","https://openalex.org/W6638306584","https://openalex.org/W6638996481","https://openalex.org/W6676755162"],"related_works":["https://openalex.org/W3031573373","https://openalex.org/W2017539237","https://openalex.org/W2607776059","https://openalex.org/W2063361377","https://openalex.org/W2802561361","https://openalex.org/W2487470953","https://openalex.org/W2415162139","https://openalex.org/W4205593364","https://openalex.org/W2945339633","https://openalex.org/W3118966479"],"abstract_inverted_index":{"The":[0],"thalamus":[1,133],"sub-cortical":[2],"gray":[3],"matter":[4],"structure":[5],"consists":[6],"of":[7,39,148,162,170],"contiguous":[8],"nuclei,":[9,41],"each":[10],"individually":[11],"responsible":[12],"for":[13],"communication":[14],"between":[15],"various":[16],"cerebral":[17],"cortex":[18],"and":[19,34,70,94,97,136,168],"midbrain":[20],"regions.":[21],"These":[22,142],"nuclei":[23,65,138],"are":[24,129],"differentially":[25],"affected":[26],"in":[27,51,74],"neurodegenerative":[28],"diseases":[29],"such":[30],"as":[31],"multiple":[32,150],"sclerosis":[33],"Alzheimer's.":[35],"However":[36],"thalamic":[37,137],"parcellation":[38],"the":[40,48,104,145,166],"manual":[42,126],"or":[43],"automatic,":[44],"is":[45],"difficult":[46],"given":[47],"limited":[49],"contrast":[50],"any":[52],"particular":[53],"magnetic":[54],"resonance":[55],"(MR)":[56],"modality.":[57],"Several":[58],"groups":[59],"have":[60],"had":[61],"qualitative":[62],"success":[63],"differentiating":[64],"based":[66],"on":[67,103,159],"spatial":[68],"location":[69],"fiber":[71],"orientation":[72],"information":[73],"diffusion":[75],"tensor":[76],"imaging":[77],"(DTI).":[78],"In":[79,108],"this":[80],"paper,":[81],"we":[82,110,118],"extend":[83],"these":[84,88],"principles":[85],"by":[86,98],"combining":[87],"discriminating":[89],"dimensions":[90],"with":[91,120],"structural":[92],"MR":[93],"derived":[95],"information,":[96],"building":[99],"random":[100],"forest":[101],"learners":[102,143],"resultant":[105],"multi-modal":[106],"features.":[107],"training,":[109],"form":[111],"a":[112,121,125,149,160],"multi-dimensional":[113],"feature":[114],"per":[115],"voxel,":[116],"which":[117],"associate":[119],"nucleus":[122],"classification":[123],"from":[124,134,139],"rater.":[127],"Learners":[128],"trained":[130],"to":[131],"differentiate":[132],"background":[135],"other":[140],"nuclei.":[141],"inform":[144],"external":[146],"forces":[147],"object":[151],"level":[152],"set":[153,161],"model.":[154],"Our":[155],"cross-validated":[156],"quantitative":[157],"results":[158],"twenty":[163],"subjects":[164],"show":[165],"efficacy":[167],"reproducibility":[169],"our":[171],"results.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
