{"id":"https://openalex.org/W4408351891","doi":"https://doi.org/10.1109/icassp49660.2025.10889040","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","display_name":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408351891","doi":"https://doi.org/10.1109/icassp49660.2025.10889040"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10889040","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889040","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5100420910","display_name":"Ziyu Wang","orcid":"https://orcid.org/0000-0001-9534-3134"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyu Wang","raw_affiliation_strings":["Tsinghua University,Department of Computer Science and Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Computer Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036539685","display_name":"Tengyu Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tengyu Pan","raw_affiliation_strings":["Tsinghua University,Department of Computer Science and Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Computer Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100330782","display_name":"Zhenyu Li","orcid":"https://orcid.org/0000-0003-2112-9834"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu Li","raw_affiliation_strings":["Tsinghua University,Department of Computer Science and Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Computer Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010193820","display_name":"Ji Wu","orcid":"https://orcid.org/0000-0002-5511-5361"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji Wu","raw_affiliation_strings":["Beihang University,School of Computer Science and Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University,School of Computer Science and Engineering,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059036409","display_name":"Xiuxing Li","orcid":"https://orcid.org/0000-0002-1178-7422"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuxing Li","raw_affiliation_strings":["Beijing Institute of Technology,School of Computer Science and Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology,School of Computer Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100630871","display_name":"Jianyong Wang","orcid":"https://orcid.org/0000-0003-1689-2384"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianyong Wang","raw_affiliation_strings":["Tsinghua University,Department of Computer Science and Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Computer Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9349,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.72281294,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9876000285148621,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9876000285148621,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.982200026512146,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9467999935150146,"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/decoding-methods","display_name":"Decoding methods","score":0.7713487148284912},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.7236826419830322},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7067378759384155},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6484032869338989},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5943406820297241},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4459910988807678},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4320720434188843},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.11501264572143555}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7713487148284912},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.7236826419830322},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7067378759384155},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6484032869338989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5943406820297241},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4459910988807678},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4320720434188843},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11501264572143555}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10889040","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889040","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1570899238","https://openalex.org/W1861492603","https://openalex.org/W2024729467","https://openalex.org/W2133665775","https://openalex.org/W2135046866","https://openalex.org/W2137526583","https://openalex.org/W2143895814","https://openalex.org/W2153156486","https://openalex.org/W2183341477","https://openalex.org/W2963363373","https://openalex.org/W3122715624","https://openalex.org/W4200613736","https://openalex.org/W4295750005","https://openalex.org/W4309408768","https://openalex.org/W4377142774","https://openalex.org/W4386881720","https://openalex.org/W6772029579","https://openalex.org/W6779997284","https://openalex.org/W6784440491","https://openalex.org/W6809885388","https://openalex.org/W6850028020","https://openalex.org/W6853649194","https://openalex.org/W6862361105"],"related_works":["https://openalex.org/W3027020613","https://openalex.org/W2016533837","https://openalex.org/W3167885074","https://openalex.org/W2892386716","https://openalex.org/W1998563493","https://openalex.org/W4306164210","https://openalex.org/W4313316311","https://openalex.org/W4362608745","https://openalex.org/W2383143032","https://openalex.org/W2082728368"],"abstract_inverted_index":{"fMRI":[0,58,83],"(functional":[1],"Magnetic":[2],"Resonance":[3],"Imaging)":[4],"visual":[5,17,59,188],"decoding":[6,8,43,60,84,103],"involves":[7],"the":[9,46,54,97,113,121,127,147,156,168,177,183,200],"original":[10],"image":[11,102],"from":[12,124],"brain":[13,31,187],"signals":[14],"elicited":[15],"by":[16],"stimuli.":[18],"This":[19,66],"often":[20],"relies":[21],"on":[22,105,176],"manually":[23],"labeled":[24,94],"ROIs":[25,35,95],"(Regions":[26],"of":[27,48,57,72,112],"Interest)":[28],"to":[29,99,144,166],"select":[30],"voxels.":[32],"However,":[33],"these":[34],"can":[36],"contain":[37],"redundant":[38],"information":[39],"and":[40,141,150,190],"noise,":[41],"reducing":[42],"performance.":[44],"Additionally,":[45],"lack":[47],"automated":[49],"ROI":[50,78,207],"labeling":[51,79],"methods":[52],"hinders":[53],"practical":[55],"application":[56],"technology,":[61],"especially":[62],"for":[63,81,116,171,186],"new":[64,117],"subjects.":[65],"work":[67],"presents":[68],"TROI":[69,92],"(Trainable":[70],"Region":[71],"Interest),":[73],"a":[74,106,132,161],"novel":[75],"two-stage,":[76],"data-driven":[77],"method":[80,135,185,198,202],"cross-subject":[82,107],"tasks,":[85],"particularly":[86],"when":[87],"subject":[88],"samples":[89],"are":[90],"limited.":[91],"leverages":[93],"in":[96],"dataset":[98,181],"pretrain":[100],"an":[101,205],"backbone":[104],"dataset,":[108],"enabling":[109],"efficient":[110],"optimization":[111],"input":[114,152,169],"layer":[115,153,170],"subjects":[118],"without":[119],"retraining":[120],"entire":[122],"model":[123],"scratch.":[125],"In":[126,155],"first":[128],"stage,":[129,158],"we":[130,159],"introduce":[131],"voxel":[133,148,196],"selection":[134,197],"that":[136,194],"combines":[137],"sparse":[138],"mask":[139,149],"training":[140],"low-pass":[142],"filtering":[143],"quickly":[145],"generate":[146],"determine":[151],"dimensions.":[154],"second":[157],"apply":[160],"learning":[162],"rate":[163],"rewinding":[164],"strategy":[165],"fine-tune":[167],"downstream":[172],"tasks.":[173],"Experimental":[174],"results":[175],"same":[178],"small":[179],"sample":[180],"as":[182],"baseline":[184],"retrieval":[189],"reconstruction":[191],"tasks":[192],"show":[193],"our":[195],"surpasses":[199],"state-of-the-art":[201],"MindEye2":[203],"with":[204],"annotated":[206],"mask.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}