{"id":"https://openalex.org/W4409411721","doi":"https://doi.org/10.3390/a18040227","title":"Prompt Once, Segment Everything: Leveraging SAM 2 Potential for Infinite Medical Image Segmentation with a Single Prompt","display_name":"Prompt Once, Segment Everything: Leveraging SAM 2 Potential for Infinite Medical Image Segmentation with a Single Prompt","publication_year":2025,"publication_date":"2025-04-14","ids":{"openalex":"https://openalex.org/W4409411721","doi":"https://doi.org/10.3390/a18040227"},"language":"en","primary_location":{"id":"doi:10.3390/a18040227","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a18040227","pdf_url":"https://www.mdpi.com/1999-4893/18/4/227/pdf?version=1744642636","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1999-4893/18/4/227/pdf?version=1744642636","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088907689","display_name":"Juan D. Guti\u00e9rrez","orcid":"https://orcid.org/0000-0002-1024-6202"},"institutions":[{"id":"https://openalex.org/I200284239","display_name":"Universidade de Santiago de Compostela","ror":"https://ror.org/030eybx10","country_code":"ES","type":"education","lineage":["https://openalex.org/I200284239"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Juan D. Guti\u00e9rrez","raw_affiliation_strings":["Department of Electronics and Computer Science, Universidad de Santiago de Compostela, R\u00faa Benigno Ledo, 27002 Lugo, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Computer Science, Universidad de Santiago de Compostela, R\u00faa Benigno Ledo, 27002 Lugo, Spain","institution_ids":["https://openalex.org/I200284239"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101779587","display_name":"Emilio Delgado","orcid":"https://orcid.org/0000-0002-9144-0698"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Emilio Delgado","raw_affiliation_strings":["Instituto de Investigaci\u00f3n en Tecnolog\u00edas Inform\u00e1ticas Aplicadas (INTIA), Universidad de Extremadura, Av. Universidad s/n, 10003 C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Instituto de Investigaci\u00f3n en Tecnolog\u00edas Inform\u00e1ticas Aplicadas (INTIA), Universidad de Extremadura, Av. Universidad s/n, 10003 C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117134799","display_name":"Carlos Breuer","orcid":null},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Carlos Breuer","raw_affiliation_strings":["Instituto de Investigaci\u00f3n en Tecnolog\u00edas Inform\u00e1ticas Aplicadas (INTIA), Universidad de Extremadura, Av. Universidad s/n, 10003 C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Instituto de Investigaci\u00f3n en Tecnolog\u00edas Inform\u00e1ticas Aplicadas (INTIA), Universidad de Extremadura, Av. Universidad s/n, 10003 C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000069622","display_name":"Jos\u00e9 M. Conejero","orcid":"https://orcid.org/0000-0003-2640-679X"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jos\u00e9 M. Conejero","raw_affiliation_strings":["Instituto de Investigaci\u00f3n en Tecnolog\u00edas Inform\u00e1ticas Aplicadas (INTIA), Universidad de Extremadura, Av. Universidad s/n, 10003 C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Instituto de Investigaci\u00f3n en Tecnolog\u00edas Inform\u00e1ticas Aplicadas (INTIA), Universidad de Extremadura, Av. Universidad s/n, 10003 C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000819463","display_name":"Roberto Rodr\u00edguez-Echeverr\u00eda","orcid":"https://orcid.org/0000-0002-6545-0913"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Roberto Rodriguez-Echeverria","raw_affiliation_strings":["Instituto de Investigaci\u00f3n en Tecnolog\u00edas Inform\u00e1ticas Aplicadas (INTIA), Universidad de Extremadura, Av. Universidad s/n, 10003 C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Instituto de Investigaci\u00f3n en Tecnolog\u00edas Inform\u00e1ticas Aplicadas (INTIA), Universidad de Extremadura, Av. Universidad s/n, 10003 C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5088907689"],"corresponding_institution_ids":["https://openalex.org/I200284239"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":4.087,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.93140643,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"18","issue":"4","first_page":"227","last_page":"227"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9986000061035156,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9986000061035156,"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":0.998199999332428,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9966999888420105,"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":0.6475368738174438},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.614760160446167},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5969873666763306},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5765156745910645},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5173491835594177},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5127214193344116}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6475368738174438},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.614760160446167},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5969873666763306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5765156745910645},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5173491835594177},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5127214193344116}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/a18040227","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a18040227","pdf_url":"https://www.mdpi.com/1999-4893/18/4/227/pdf?version=1744642636","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3d0acb6f713249c09196f4823c26c506","is_oa":true,"landing_page_url":"https://doaj.org/article/3d0acb6f713249c09196f4823c26c506","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 18, Iss 4, p 227 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/a18040227","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a18040227","pdf_url":"https://www.mdpi.com/1999-4893/18/4/227/pdf?version=1744642636","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4409411721.pdf"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1904878066","https://openalex.org/W2009911194","https://openalex.org/W2050622035","https://openalex.org/W2099707769","https://openalex.org/W2108281845","https://openalex.org/W2118386984","https://openalex.org/W2142514727","https://openalex.org/W2732931556","https://openalex.org/W2763160469","https://openalex.org/W2937845726","https://openalex.org/W2980998394","https://openalex.org/W2999978966","https://openalex.org/W3018760686","https://openalex.org/W3022273241","https://openalex.org/W3026637813","https://openalex.org/W3047502985","https://openalex.org/W3085467444","https://openalex.org/W3092622437","https://openalex.org/W3108591672","https://openalex.org/W3115781494","https://openalex.org/W3159178846","https://openalex.org/W3174846316","https://openalex.org/W3185556852","https://openalex.org/W4205172069","https://openalex.org/W4221126236","https://openalex.org/W4225271274","https://openalex.org/W4283072464","https://openalex.org/W4283160212","https://openalex.org/W4319444096","https://openalex.org/W4382238821","https://openalex.org/W4387307449","https://openalex.org/W4389430914","https://openalex.org/W4390738672","https://openalex.org/W4390874575","https://openalex.org/W4391069643","https://openalex.org/W4391109864","https://openalex.org/W4392203599","https://openalex.org/W4392662056","https://openalex.org/W4400342280","https://openalex.org/W4401075918","https://openalex.org/W4402425777","https://openalex.org/W4402781391","https://openalex.org/W4403013301","https://openalex.org/W4405104133","https://openalex.org/W6639867372","https://openalex.org/W6797026944","https://openalex.org/W6839656003"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Semantic":[0],"segmentation":[1,20,71,88,132,157,190,196,255],"of":[2,28,100,169,200,207,223,229,294],"medical":[3,31,101,113,208],"images":[4,209],"holds":[5],"significant":[6],"potential":[7],"for":[8,67,248],"enhancing":[9],"diagnostic":[10],"and":[11,25,50,69,108,123,131,146,156,175,268],"surgical":[12],"procedures.":[13],"Radiology":[14],"specialists":[15,258],"can":[16],"benefit":[17],"from":[18,287],"automated":[19],"tools":[21],"that":[22,162,214],"facilitate":[23],"identifying":[24],"isolating":[26],"regions":[27],"interest":[29],"in":[30,112,171,177,189],"scans.":[32],"Nevertheless,":[33],"to":[34,43,90,95,128,182,195,203,218,240,259,263,271,281,290],"obtain":[35,272],"precise":[36],"results,":[37],"sophisticated":[38],"deep":[39,284],"learning":[40,285],"models":[41,245],"tailored":[42],"this":[44,249],"specific":[45],"task":[46],"must":[47],"be":[48],"developed":[49],"trained,":[51],"a":[52,63,81,186,205,224,230,234,283],"capability":[53],"not":[54],"universally":[55],"accessible.":[56],"Segment":[57],"Anything":[58],"Model":[59],"(SAM)":[60],"2":[61,164],"is":[62,138,216],"foundational":[64],"model":[65,286,299],"designed":[66],"image":[68,114],"video":[70,87],"tasks,":[72],"built":[73],"on":[74,150],"its":[75],"predecessor,":[76],"SAM.":[77],"This":[78],"paper":[79],"introduces":[80],"novel":[82,136,193],"approach":[83,137,194,252],"leveraging":[84],"SAM":[85,107,109,163],"2\u2019s":[86,110],"capabilities":[89],"reduce":[91],"the":[92,120,151,172,178,198,221,254,292],"prompts":[93,201],"required":[94],"segment":[96,204,219],"an":[97,166,295],"entire":[98],"volume":[99,206,225],"images.":[102],"The":[103,159,266],"study":[104],"first":[105],"compares":[106],"performance":[111],"segmentation.":[115],"Evaluation":[116],"metrics":[117],"such":[118],"as":[119],"Jaccard":[121,173],"index":[122,174],"Dice":[124,179],"score":[125,180],"are":[126,275],"used":[127],"measure":[129],"precision":[130,144],"quality.":[133],"Then,":[134],"our":[135],"introduced.":[139],"Statistical":[140],"tests":[141],"include":[142],"comparing":[143],"gains":[145],"computational":[147],"efficiency,":[148],"focusing":[149],"trade-off":[152],"between":[153],"resource":[154],"use":[155],"time.":[158,191],"results":[160,238,274],"show":[161],"achieves":[165],"average":[167],"improvement":[168],"1.76%":[170],"1.49%":[176],"compared":[181],"SAM,":[183],"albeit":[184],"with":[185,233],"ten-fold":[187],"increase":[188],"Our":[192,251],"reduces":[197],"number":[199],"needed":[202,280],"by":[210,243],"99.95%.":[211],"We":[212],"demonstrate":[213],"it":[215],"possible":[217],"all":[220],"slices":[222],"and,":[226],"even":[227],"more,":[228],"whole":[231],"dataset,":[232],"single":[235],"prompt,":[236],"achieving":[237],"comparable":[239],"those":[241,279],"obtained":[242],"state-of-the-art":[244],"explicitly":[246],"trained":[247],"task.":[250],"simplifies":[253],"process,":[256],"allowing":[257],"devote":[260],"more":[261],"time":[262],"other":[264],"tasks.":[265],"hardware":[267],"personnel":[269],"requirements":[270],"these":[273],"much":[276],"lower":[277],"than":[278],"train":[282],"scratch":[288],"or":[289],"modify":[291],"behavior":[293],"existing":[296],"one":[297],"using":[298],"modification":[300],"techniques.":[301]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
