{"id":"https://openalex.org/W4414798862","doi":"https://doi.org/10.1109/access.2025.3617567","title":"Self-Supervised Depth Estimation and 3D Reconstruction With Layer-Wise LoRA of Foundation Model in Endoscopy","display_name":"Self-Supervised Depth Estimation and 3D Reconstruction With Layer-Wise LoRA of Foundation Model in Endoscopy","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414798862","doi":"https://doi.org/10.1109/access.2025.3617567"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3617567","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3617567","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3617567","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027723964","display_name":"Saad Khalil","orcid":"https://orcid.org/0009-0000-7828-4339"},"institutions":[{"id":"https://openalex.org/I163753206","display_name":"Chungbuk National University","ror":"https://ror.org/02wnxgj78","country_code":"KR","type":"education","lineage":["https://openalex.org/I163753206"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Saad Khalil","raw_affiliation_strings":["Department of Intelligent Systems and Robotics, Chungbuk National University, Cheongju, South Korea"],"raw_orcid":"https://orcid.org/0009-0000-7828-4339","affiliations":[{"raw_affiliation_string":"Department of Intelligent Systems and Robotics, Chungbuk National University, Cheongju, South Korea","institution_ids":["https://openalex.org/I163753206"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071134845","display_name":"S.P. Kim","orcid":"https://orcid.org/0009-0001-3753-0481"},"institutions":[{"id":"https://openalex.org/I4210160144","display_name":"The Catholic University of Korea Seoul St. Mary's Hospital","ror":"https://ror.org/056cn0e37","country_code":"KR","type":"healthcare","lineage":["https://openalex.org/I4210160144","https://openalex.org/I4405260414","https://openalex.org/I87111246"]},{"id":"https://openalex.org/I87111246","display_name":"Catholic University of Korea","ror":"https://ror.org/01fpnj063","country_code":"KR","type":"education","lineage":["https://openalex.org/I87111246"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sol Kim","raw_affiliation_strings":["Department of Internal Medicine, Seoul St. Maryâs Hospital, Division of Gastroenterology, The Catholic University of Korea, Seoul, South Korea","Department of Internal Medicine, The Catholic University of Korea, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Internal Medicine, Seoul St. Maryâs Hospital, Division of Gastroenterology, The Catholic University of Korea, Seoul, South Korea","institution_ids":["https://openalex.org/I4210160144"]},{"raw_affiliation_string":"Department of Internal Medicine, The Catholic University of Korea, Seoul, South Korea","institution_ids":["https://openalex.org/I87111246"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037549135","display_name":"Bo\u2010In Lee","orcid":"https://orcid.org/0000-0002-0218-4136"},"institutions":[{"id":"https://openalex.org/I4210160144","display_name":"The Catholic University of Korea Seoul St. Mary's Hospital","ror":"https://ror.org/056cn0e37","country_code":"KR","type":"healthcare","lineage":["https://openalex.org/I4210160144","https://openalex.org/I4405260414","https://openalex.org/I87111246"]},{"id":"https://openalex.org/I87111246","display_name":"Catholic University of Korea","ror":"https://ror.org/01fpnj063","country_code":"KR","type":"education","lineage":["https://openalex.org/I87111246"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Bo-In Lee","raw_affiliation_strings":["Department of Internal Medicine, Seoul St. Maryâs Hospital, Division of Gastroenterology, The Catholic University of Korea, Seoul, South Korea","Department of Internal Medicine, The Catholic University of Korea, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Internal Medicine, Seoul St. Maryâs Hospital, Division of Gastroenterology, The Catholic University of Korea, Seoul, South Korea","institution_ids":["https://openalex.org/I4210160144"]},{"raw_affiliation_string":"Department of Internal Medicine, The Catholic University of Korea, Seoul, South Korea","institution_ids":["https://openalex.org/I87111246"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060901163","display_name":"Youngbae Hwang","orcid":"https://orcid.org/0000-0002-3400-0493"},"institutions":[{"id":"https://openalex.org/I163753206","display_name":"Chungbuk National University","ror":"https://ror.org/02wnxgj78","country_code":"KR","type":"education","lineage":["https://openalex.org/I163753206"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngbae Hwang","raw_affiliation_strings":["Department of Intelligent Systems and Robotics, Chungbuk National University, Cheongju, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-3400-0493","affiliations":[{"raw_affiliation_string":"Department of Intelligent Systems and Robotics, Chungbuk National University, Cheongju, South Korea","institution_ids":["https://openalex.org/I163753206"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.7335,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.77067821,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"13","issue":null,"first_page":"173334","last_page":"173346"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.7552000284194946,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.7552000284194946,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6378999948501587},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.5214999914169312},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.4790000021457672},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4327000081539154},{"id":"https://openalex.org/keywords/bundle-adjustment","display_name":"Bundle adjustment","score":0.42480000853538513},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.38359999656677246},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.38190001249313354},{"id":"https://openalex.org/keywords/brightness","display_name":"Brightness","score":0.38040000200271606}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8130999803543091},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6378999948501587},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.613099992275238},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5892000198364258},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.5214999914169312},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.4790000021457672},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4327000081539154},{"id":"https://openalex.org/C179458375","wikidata":"https://www.wikidata.org/wiki/Q1020763","display_name":"Bundle adjustment","level":3,"score":0.42480000853538513},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.38359999656677246},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.38190001249313354},{"id":"https://openalex.org/C125245961","wikidata":"https://www.wikidata.org/wiki/Q221656","display_name":"Brightness","level":2,"score":0.38040000200271606},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.3743000030517578},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3361999988555908},{"id":"https://openalex.org/C23903533","wikidata":"https://www.wikidata.org/wiki/Q17122739","display_name":"Reprojection error","level":3,"score":0.3102000057697296},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C134652429","wikidata":"https://www.wikidata.org/wiki/Q1052698","display_name":"Jitter","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.2533000111579895}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3617567","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3617567","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:01104f8046684f9ebe6f3b5a259aea04","is_oa":true,"landing_page_url":"https://doaj.org/article/01104f8046684f9ebe6f3b5a259aea04","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 173334-173346 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3617567","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3617567","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2542981700","display_name":null,"funder_award_id":"RS-2024-00425661","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G7575369263","display_name":null,"funder_award_id":"RS-2021-II212068","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G8088698451","display_name":null,"funder_award_id":"IITP-2024-2020-0-01462","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"}],"funders":[{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Depth":[0],"estimation":[1,22,51,187],"is":[2,135],"crucial":[3],"for":[4,13,23,48,69,83,142,185],"3D":[5,110,208],"reconstruction":[6],"and":[7,97,160,168,201],"surgical":[8],"navigation,":[9],"providing":[10],"critical":[11],"insights":[12],"endoscopic":[14,70,195],"procedures.":[15],"While":[16],"foundation":[17,66,183],"models":[18],"excel":[19],"in":[20,28,188,194,215],"depth":[21,50,118,162,186],"natural":[24],"images,":[25],"their":[26],"performance":[27,153,214],"the":[29,64,77,132,139,147,151,182,189],"medical":[30,190],"domain":[31],"remains":[32],"limited,":[33],"particularly":[34],"under":[35],"challenging":[36],"conditions":[37],"like":[38],"brightness":[39,122,199],"fluctuations.":[40],"This":[41],"study":[42],"develops":[43],"a":[44,58,98,121],"robust":[45],"self-supervised":[46],"framework":[47,179],"monocular":[49],"to":[52,93,103],"address":[53],"these":[54],"challenges.":[55],"We":[56],"introduce":[57],"layer-wise":[59],"low-rank":[60],"adaptation":[61],"(LW-LoRA)":[62],"of":[63,154],"Depth-Anything-V2":[65],"model,":[67],"tailored":[68],"data.":[71],"Unlike":[72],"conventional":[73],"fine-tuning,":[74],"LW-LoRA":[75],"adjusts":[76],"LoRA":[78,140],"rank":[79],"across":[80,174],"encoder":[81,134],"layers":[82,141],"efficient":[84],"training.":[85],"The":[86],"method":[87],"integrates":[88],"residual":[89],"convolutional":[90],"blocks":[91],"(ResConv)":[92],"capture":[94],"fine-grained":[95],"details":[96],"multi-head":[99],"attention-based":[100],"pose":[101,106],"network":[102],"enhance":[104],"camera":[105],"estimation,":[107],"ensuring":[108,212],"accurate":[109],"reconstructions.":[111],"A":[112],"multi-scale":[113],"SSIM-based":[114],"reprojection":[115],"loss":[116],"refines":[117],"predictions,":[119],"while":[120],"calibration":[123],"module":[124],"ensures":[125],"robustness":[126],"against":[127],"illumination":[128],"inconsistencies.":[129],"During":[130],"training,":[131],"backbone":[133],"frozen,":[136],"optimizing":[137],"only":[138],"efficiency.":[143],"Extensive":[144],"evaluations":[145],"on":[146,166],"SCARED":[148],"dataset":[149],"highlight":[150],"superior":[152],"our":[155],"framework,":[156],"offering":[157],"faster":[158],"inference":[159],"high-quality":[161],"maps.":[163],"Zero-shot":[164],"testing":[165],"Hamlyn":[167],"clinical":[169,216],"datasets":[170],"confirms":[171],"its":[172],"generalization":[173],"diverse":[175],"data":[176],"types.":[177],"Our":[178],"efficiently":[180],"adapts":[181],"model":[184],"domain,":[191],"addressing":[192],"challenges":[193],"imaging,":[196],"such":[197],"as":[198],"variations":[200],"fine-detail":[202],"preservation.":[203],"It":[204],"enables":[205],"accurate,":[206],"dense":[207],"point":[209],"cloud":[210],"reconstructions,":[211],"reliable":[213],"settings.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}