{"id":"https://openalex.org/W4388555917","doi":"https://doi.org/10.48550/arxiv.2311.04847","title":"Are foundation models efficient for medical image segmentation?","display_name":"Are foundation models efficient for medical image segmentation?","publication_year":2023,"publication_date":"2023-11-08","ids":{"openalex":"https://openalex.org/W4388555917","doi":"https://doi.org/10.48550/arxiv.2311.04847"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2311.04847","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.04847","pdf_url":"https://arxiv.org/pdf/2311.04847","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":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2311.04847","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056972047","display_name":"Danielle Ferreira","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ferreira, Danielle","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5064018474","display_name":"Rima Arnaout","orcid":"https://orcid.org/0000-0002-7134-0040"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arnaout, Rima","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5056972047"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9945999979972839,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9945999979972839,"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/T10862","display_name":"AI in cancer detection","score":0.9929999709129333,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9879999756813049,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7594461441040039},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.6934453845024109},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.6733611822128296},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6402998566627502},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5963470339775085},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5415156483650208},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49372801184654236},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4595796465873718},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4365800619125366},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3822252154350281},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38015225529670715},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.09761026501655579},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07223096489906311}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7594461441040039},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.6934453845024109},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.6733611822128296},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6402998566627502},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5963470339775085},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5415156483650208},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49372801184654236},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4595796465873718},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4365800619125366},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3822252154350281},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38015225529670715},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.09761026501655579},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07223096489906311},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2311.04847","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.04847","pdf_url":"https://arxiv.org/pdf/2311.04847","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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2311.04847","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2311.04847","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-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2311.04847","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.04847","pdf_url":"https://arxiv.org/pdf/2311.04847","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388555917.pdf","grobid_xml":"https://content.openalex.org/works/W4388555917.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2368605798","https://openalex.org/W2518037665","https://openalex.org/W2348524959","https://openalex.org/W2477036161","https://openalex.org/W2368049389","https://openalex.org/W2384861574","https://openalex.org/W4294565801","https://openalex.org/W2170801710","https://openalex.org/W1997160662","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Foundation":[0],"models":[1],"are":[2],"experiencing":[3],"a":[4,18,44],"surge":[5],"in":[6],"popularity.":[7],"The":[8],"Segment":[9],"Anything":[10],"model":[11],"(SAM)":[12],"asserts":[13],"an":[14],"ability":[15],"to":[16,43],"segment":[17],"wide":[19],"spectrum":[20],"of":[21],"objects":[22],"but":[23],"required":[24,62],"supervised":[25],"training":[26],"at":[27],"unprecedented":[28],"scale.":[29],"We":[30],"compared":[31],"SAM's":[32],"performance":[33],"(against":[34],"clinical":[35],"ground":[36],"truth)":[37],"and":[38,61,66],"resources":[39],"(labeling":[40],"time,":[41],"compute)":[42],"modality-specific,":[45],"label-free":[46],"self-supervised":[47],"learning":[48],"(SSL)":[49],"method":[50],"on":[51],"25":[52],"measurements":[53],"for":[54],"100":[55],"cardiac":[56],"ultrasounds.":[57],"SAM":[58],"performed":[59],"poorly":[60],"significantly":[63],"more":[64],"labeling":[65],"computing":[67],"resources,":[68],"demonstrating":[69],"worse":[70],"efficiency":[71],"than":[72],"SSL.":[73]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
