{"id":"https://openalex.org/W4406259791","doi":"https://doi.org/10.1109/bibm62325.2024.10822764","title":"DEAP-3DSAM: Decoder Enhanced and Auto Prompt SAM for 3D Medical Image Segmentation","display_name":"DEAP-3DSAM: Decoder Enhanced and Auto Prompt SAM for 3D Medical Image Segmentation","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406259791","doi":"https://doi.org/10.1109/bibm62325.2024.10822764"},"language":"en","primary_location":{"id":"doi:10.1109/bibm62325.2024.10822764","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822764","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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":null,"display_name":"Fangda Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fangda Chen","raw_affiliation_strings":["National University of Defense Tech.,College of Computer Science and Tech.,Changsha,China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Tech.,College of Computer Science and Tech.,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102152035","display_name":"Jintao Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jintao Tang","raw_affiliation_strings":["National University of Defense Tech.,College of Computer Science and Tech.,Changsha,China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Tech.,College of Computer Science and Tech.,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002937390","display_name":"Pancheng Wang","orcid":"https://orcid.org/0000-0002-4450-8848"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pancheng Wang","raw_affiliation_strings":["National University of Defense Tech.,College of Computer Science and Tech.,Changsha,China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Tech.,College of Computer Science and Tech.,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112109933","display_name":"Ting Wang","orcid":"https://orcid.org/0000-0001-9553-5232"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Wang","raw_affiliation_strings":["National University of Defense Tech.,College of Computer Science and Tech.,Changsha,China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Tech.,College of Computer Science and Tech.,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100376019","display_name":"Shasha Li","orcid":"https://orcid.org/0000-0002-6508-5119"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shasha Li","raw_affiliation_strings":["National University of Defense Tech.,College of Computer Science and Tech.,Changsha,China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Tech.,College of Computer Science and Tech.,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003501766","display_name":"Ting Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ting Deng","raw_affiliation_strings":["TMUCIH, NCRCC,Department of GI Medical Oncology,China"],"affiliations":[{"raw_affiliation_string":"TMUCIH, NCRCC,Department of GI Medical Oncology,China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":1.1922,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.80246591,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1852","last_page":"1859"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9783999919891357,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9783999919891357,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"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/T10862","display_name":"AI in cancer detection","score":0.9725000262260437,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9629999995231628,"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/computer-science","display_name":"Computer science","score":0.7622995376586914},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6700556874275208},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6471096277236938},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6262284517288208},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5720489025115967},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4715048372745514}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7622995376586914},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6700556874275208},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6471096277236938},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6262284517288208},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5720489025115967},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4715048372745514}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm62325.2024.10822764","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822764","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"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":24,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2955058313","https://openalex.org/W3014974815","https://openalex.org/W3138516171","https://openalex.org/W3203841574","https://openalex.org/W4212875960","https://openalex.org/W4221163766","https://openalex.org/W4390874575","https://openalex.org/W4390970074","https://openalex.org/W4390971106","https://openalex.org/W4390971133","https://openalex.org/W4390971251","https://openalex.org/W4396783545","https://openalex.org/W4403828029","https://openalex.org/W6779163297","https://openalex.org/W6796581206","https://openalex.org/W6801350836","https://openalex.org/W6802744804","https://openalex.org/W6845563047","https://openalex.org/W6851607685","https://openalex.org/W6851980744","https://openalex.org/W6853207815","https://openalex.org/W6856792011","https://openalex.org/W6858031465"],"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":{"The":[0,144],"Segment":[1],"Anything":[2],"Model":[3],"(SAM)":[4],"has":[5],"recently":[6],"demonstrated":[7],"significant":[8],"potential":[9],"in":[10,44,65,153],"medical":[11,31],"image":[12,32,103,155],"segmentation.":[13,33],"Although":[14],"SAM":[15,42,86],"is":[16],"primarily":[17],"trained":[18],"on":[19,57,137],"2D":[20],"images,":[21],"attempts":[22],"have":[23],"been":[24],"made":[25],"to":[26,29,40,63,88,111,122],"apply":[27],"it":[28],"3D":[30,37,154],"However,":[34],"the":[35,80,101,172],"pseudo":[36],"processing":[38],"used":[39],"adapt":[41],"results":[43,145],"spatial":[45,109,113],"feature":[46],"loss,":[47],"limiting":[48],"its":[49],"performance.":[50],"Additionally,":[51],"most":[52],"SAM-based":[53],"methods":[54],"still":[55],"rely":[56],"manual":[58,161],"prompts,":[59],"which":[60],"are":[61],"challenging":[62],"implement":[64],"real-world":[66],"scenarios":[67],"and":[68,83,107,130,167],"require":[69],"extensive":[70],"external":[71],"expert":[72],"knowledge.":[73],"To":[74],"address":[75],"these":[76,90],"limitations,":[77],"we":[78,93],"introduce":[79],"Decoder":[81,98],"Enhanced":[82,97],"Auto":[84],"Prompt":[85],"(DEAP-3DSAM)":[87],"tackle":[89],"limitations.":[91],"Specifically,":[92],"propose":[94],"a":[95,118],"Feature":[96],"that":[99,147],"fuses":[100],"original":[102],"features":[104],"with":[105],"rich":[106],"detailed":[108],"information":[110,126],"enhance":[112],"features.":[114],"We":[115,133],"also":[116],"design":[117],"Dual":[119],"Attention":[120,129],"Prompter":[121],"automatically":[123],"obtain":[124],"prompt":[125,162],"through":[127],"Spatial":[128],"Channel":[131],"Attention.":[132],"conduct":[134],"comprehensive":[135],"experiments":[136],"four":[138],"public":[139],"abdominal":[140],"tumor":[141],"segmentation":[142],"datasets.":[143],"indicate":[146],"our":[148,175],"DEAP-3DSAM":[149],"achieves":[150],"state-of-the-art":[151],"performance":[152],"segmentation,":[156],"outperforming":[157],"or":[158],"matching":[159],"existing":[160],"methods.":[163],"Furthermore,":[164],"both":[165],"quantitative":[166],"qualitative":[168],"ablation":[169],"studies":[170],"confirm":[171],"effectiveness":[173],"of":[174],"proposed":[176],"modules.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4}],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}