{"id":"https://openalex.org/W4391272458","doi":"https://doi.org/10.48550/arxiv.2401.13961","title":"TriSAM: Tri-Plane SAM for zero-shot cortical blood vessel segmentation in VEM images","display_name":"TriSAM: Tri-Plane SAM for zero-shot cortical blood vessel segmentation in VEM images","publication_year":2024,"publication_date":"2024-01-25","ids":{"openalex":"https://openalex.org/W4391272458","doi":"https://doi.org/10.48550/arxiv.2401.13961"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2401.13961","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2401.13961","pdf_url":"https://arxiv.org/pdf/2401.13961","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2401.13961","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102220614","display_name":"Jia Wan","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wan, Jia","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082419115","display_name":"Wanhua Li","orcid":"https://orcid.org/0000-0002-2730-0543"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Wanhua","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015496269","display_name":"Atmadeep Banerjee","orcid":"https://orcid.org/0009-0008-7949-8062"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Adhinarta, Jason Ken","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056837622","display_name":"Jason Ken Adhinarta","orcid":"https://orcid.org/0000-0002-6247-7475"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Banerjee, Atmadeep","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090268234","display_name":"Evelina Sj\u00f6stedt","orcid":"https://orcid.org/0000-0002-0327-7377"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sjostedt, Evelina","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047394906","display_name":"Jingpeng Wu","orcid":"https://orcid.org/0000-0003-1604-8802"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Jingpeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037495122","display_name":"Jeff W. Lichtman","orcid":"https://orcid.org/0000-0002-0208-3212"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lichtman, Jeff","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043151044","display_name":"Hanspeter Pfister","orcid":"https://orcid.org/0000-0002-3620-2582"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pfister, Hanspeter","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5085365474","display_name":"Donglai Wei","orcid":"https://orcid.org/0000-0002-2329-5484"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Donglai","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5102220614"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T10857","display_name":"Advanced Electron Microscopy Techniques and Applications","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1315","display_name":"Structural Biology"},"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"}},"topics":[{"id":"https://openalex.org/T10857","display_name":"Advanced Electron Microscopy Techniques and Applications","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1315","display_name":"Structural Biology"},"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"}},{"id":"https://openalex.org/T12039","display_name":"Electron and X-Ray Spectroscopy Techniques","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/2508","display_name":"Surfaces, Coatings and Films"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9868999719619751,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.8565287590026855},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.8135545253753662},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6506749391555786},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6424828767776489},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.547123372554779},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5270060896873474},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43287935853004456},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.4242286682128906},{"id":"https://openalex.org/keywords/microscale-chemistry","display_name":"Microscale chemistry","score":0.41184067726135254},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32295018434524536},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.1568739116191864},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12726962566375732},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09653788805007935},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07368788123130798}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8565287590026855},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8135545253753662},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6506749391555786},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6424828767776489},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.547123372554779},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5270060896873474},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43287935853004456},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.4242286682128906},{"id":"https://openalex.org/C179428855","wikidata":"https://www.wikidata.org/wiki/Q1069216","display_name":"Microscale chemistry","level":2,"score":0.41184067726135254},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32295018434524536},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.1568739116191864},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12726962566375732},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09653788805007935},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07368788123130798},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2401.13961","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2401.13961","pdf_url":"https://arxiv.org/pdf/2401.13961","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2401.13961","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2401.13961","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2401.13961","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2401.13961","pdf_url":"https://arxiv.org/pdf/2401.13961","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5899999737739563,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391272458.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W1979808816","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2378045033","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687"],"abstract_inverted_index":{"While":[0],"imaging":[1,83],"techniques":[2],"at":[3,192],"macro":[4],"and":[5,11,76,85,93,187],"mesoscales":[6],"have":[7],"garnered":[8],"substantial":[9],"attention":[10],"resources,":[12],"microscale":[13],"Volume":[14],"Electron":[15],"Microscopy":[16],"(vEM)":[17],"imaging,":[18],"capable":[19],"of":[20,42,141],"revealing":[21],"intricate":[22],"vascular":[23],"details,":[24],"has":[25],"lacked":[26],"the":[27,46,80,115,139,178],"necessary":[28],"benchmarking":[29],"infrastructure.":[30],"In":[31],"this":[32,40],"paper,":[33],"we":[34,102],"address":[35],"a":[36,104,134],"significant":[37],"gap":[38],"in":[39,58],"field":[41],"neuroimaging":[43],"by":[44],"introducing":[45],"first-in-class":[47],"public":[48],"benchmark,":[49],"BvEM,":[50],"designed":[51],"specifically":[52],"for":[53,120,145],"cortical":[54,106],"blood":[55,88,107,161],"vessel":[56,108,162],"segmentation":[57,109,117,163],"vEM":[59,67],"images.":[60],"Our":[61,184],"BvEM":[62,179],"benchmark":[63,180],"is":[64],"based":[65],"on":[66,177],"image":[68,143],"volumes":[69],"from":[70,126],"three":[71,182],"mammals:":[72],"adult":[73],"mouse,":[74],"macaque,":[75],"human.":[77],"We":[78],"standardized":[79],"resolution,":[81],"addressed":[82],"variations,":[84],"meticulously":[86],"annotated":[87],"vessels":[89],"through":[90],"semi-automatic,":[91],"manual,":[92],"quality":[94],"control":[95],"processes,":[96],"ensuring":[97],"high-quality":[98],"3D":[99,121,129,160],"segmentation.":[100,122],"Furthermore,":[101],"developed":[103],"zero-shot":[105],"method":[110],"named":[111],"TriSAM,":[112],"which":[113],"leverages":[114],"powerful":[116],"model":[118,165,188],"SAM":[119,125],"To":[123],"extend":[124],"2D":[127],"to":[128,150],"volume":[130],"segmentation,":[131],"TriSAM":[132,173],"employs":[133],"multi-seed":[135],"tracking":[136,146],"framework,":[137],"leveraging":[138],"reliability":[140],"certain":[142],"planes":[144],"while":[147],"using":[148],"others":[149],"identify":[151],"potential":[152],"turning":[153],"points.":[154],"This":[155],"approach":[156],"effectively":[157],"achieves":[158],"long-term":[159],"without":[164],"training":[166],"or":[167],"fine-tuning.":[168],"Experimental":[169],"results":[170],"show":[171],"that":[172],"achieved":[174],"superior":[175],"performances":[176],"across":[181],"species.":[183],"dataset,":[185],"code,":[186],"are":[189],"available":[190],"online":[191],"\\url{https://jia-wan.github.io/bvem}.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-11T14:59:36.786465","created_date":"2024-01-27T00:00:00"}
