{"id":"https://openalex.org/W7126070710","doi":"https://doi.org/10.1109/bibm66473.2025.11356812","title":"H3DE-Net: Efficient and Accurate 3D Landmark Detection in Medical Imaging","display_name":"H3DE-Net: Efficient and Accurate 3D Landmark Detection in Medical Imaging","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126070710","doi":"https://doi.org/10.1109/bibm66473.2025.11356812"},"language":"en","primary_location":{"id":"doi:10.1109/bibm66473.2025.11356812","doi":"https://doi.org/10.1109/bibm66473.2025.11356812","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356812","pdf_url":null,"source":{"id":"https://openalex.org/S4363607730","display_name":"IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"parent_works":[],"lineage":["https://openalex.org/W7126070710"],"child_works_count":0,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2502.14221","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124209859","display_name":"Zhen Huang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Huang","raw_affiliation_strings":["School of Computer Science USTC,Hefei,Anhui,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science USTC,Hefei,Anhui,China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5153071190","display_name":"Tao Tang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Tang","raw_affiliation_strings":["School of Computer Science and Engineering UESTC,Chengdu,Sichuan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering UESTC,Chengdu,Sichuan,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007764903","display_name":"Ronghao Xu","orcid":"https://orcid.org/0009-0005-5838-0469","observed_orcids":["https://orcid.org/0009-0005-5838-0469"]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ronghao Xu","raw_affiliation_strings":["School of Computer Science USTC,Hefei,Anhui,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science USTC,Hefei,Anhui,China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124291723","display_name":"Yangbo Wei","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangbo Wei","raw_affiliation_strings":["Shanghai Jiao Tong University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053365003","display_name":"Wenkai Yang","orcid":"https://orcid.org/0009-0006-0862-4936","observed_orcids":["https://orcid.org/0009-0006-0862-4936","https://orcid.org/0000-0003-1942-7998","https://orcid.org/0009-0001-0356-2995","https://orcid.org/0009-0000-2376-1425"]},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenkai Yang","raw_affiliation_strings":["ShanghaiTech University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ShanghaiTech University,Shanghai,China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120964650","display_name":"Suhua Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405281628","display_name":"Changchun Humanities and Sciences College","ror":"https://ror.org/04na8wr11","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405281628"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Suhua Wang","raw_affiliation_strings":["Changchun Humanities and Sciences College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Changchun Humanities and Sciences College","institution_ids":["https://openalex.org/I4405281628"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124276744","display_name":"Xiaoxin Sun","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I184983240","display_name":"Northeast Normal University","ror":"https://ror.org/02rkvz144","country_code":"CN","type":"education","lineage":["https://openalex.org/I184983240"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxin Sun","raw_affiliation_strings":["School of Information Science, NENU,Changchun,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science, NENU,Changchun,China","institution_ids":["https://openalex.org/I184983240"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038318511","display_name":"Han Li","orcid":"https://orcid.org/0000-0003-2298-332X","observed_orcids":["https://orcid.org/0000-0003-2298-332X"]},"institutions":[{"id":"https://openalex.org/I4403386549","display_name":"Munich Center for Machine Learning","ror":"https://ror.org/02nfy3535","country_code":"DE","type":"education","lineage":["https://openalex.org/I4403386549","https://openalex.org/I62916508","https://openalex.org/I8204097"]},{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Han Li","raw_affiliation_strings":["Technical University of Munich (TUM) Munich Center for Machine Learning (MCML)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Munich (TUM) Munich Center for Machine Learning (MCML)","institution_ids":["https://openalex.org/I4403386549","https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":null,"display_name":"Qingsong Yao","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qingsong Yao","raw_affiliation_strings":["Stanford University,Stanford,CA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University,Stanford,CA,USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":9,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":15.1099,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.99235499,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3710","last_page":"3715"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.7627000212669373,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.7627000212669373,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.20419999957084656,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.006500000134110451,"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/medical-image-analysis","display_name":"medical image analysis","score":0.6349999904632568},{"id":"https://openalex.org/keywords/volumetric-data","display_name":"volumetric data","score":0.7239999771118164},{"id":"https://openalex.org/keywords/hybrid-cnn-transformer-model","display_name":"CNN-Transformer hybrid","score":0.7599999904632568},{"id":"https://openalex.org/keywords/attention-mechanism","display_name":"attention mechanism","score":0.6949999928474426},{"id":"https://openalex.org/keywords/bi-level-routing-attention","display_name":"bi-level routing attention","score":0.8159999847412109},{"id":"https://openalex.org/keywords/multiscale-feature-fusion","display_name":"multi-scale feature fusion","score":0.9800000190734863},{"id":"https://openalex.org/keywords/ct-images","display_name":"CT images","score":0.6269999742507935},{"id":"https://openalex.org/keywords/surgical-navigation","display_name":"surgical navigation","score":0.8849999904632568},{"id":"https://openalex.org/keywords/anatomical-variation","display_name":"anatomical variation","score":0.7900000214576721}],"concepts":[{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.8860999941825867},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7753999829292297},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6866000294685364},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5677000284194946},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.5246000289916992},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5175999999046326},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48260000348091125},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46149998903274536},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.45489999651908875},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.41609999537467957},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36739999055862427},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.33079999685287476},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3224000036716461},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3000999987125397},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2980000078678131},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.29249998927116394},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356812","doi":"https://doi.org/10.1109/bibm66473.2025.11356812","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356812","pdf_url":null,"source":{"id":"https://openalex.org/S4363607730","display_name":"IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2502.14221","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2502.14221","pdf_url":"https://arxiv.org/pdf/2502.14221","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2502.14221","doi":"https://doi.org/10.48550/arxiv.2502.14221","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2502.14221","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2502.14221","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2502.14221","pdf_url":"https://arxiv.org/pdf/2502.14221","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.428600013256073}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7126070710.pdf","grobid_xml":"https://content.openalex.org/works/W7126070710.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1995003188","https://openalex.org/W2067399451","https://openalex.org/W2432481613","https://openalex.org/W2464708700","https://openalex.org/W2621042378","https://openalex.org/W2916798096","https://openalex.org/W2925288829","https://openalex.org/W2990306149","https://openalex.org/W3094502228","https://openalex.org/W3127751679","https://openalex.org/W3194199857","https://openalex.org/W4221145195","https://openalex.org/W4367190566","https://openalex.org/W4384159609","https://openalex.org/W4385474538","https://openalex.org/W4386075524","https://openalex.org/W4388767053","https://openalex.org/W4392861990","https://openalex.org/W4402259323","https://openalex.org/W4406261673","https://openalex.org/W4408359734","https://openalex.org/W4410284330"],"related_works":["https://openalex.org/W3009170070","https://openalex.org/W4405254194","https://openalex.org/W4417246773","https://openalex.org/W7140398082","https://openalex.org/W3215951211","https://openalex.org/W3202812481","https://openalex.org/W4411460580","https://openalex.org/W2399244897","https://openalex.org/W1039922802","https://openalex.org/W2735224896"],"abstract_inverted_index":{"Landmark":[0],"detection":[1,140],"is":[2,149],"essential":[3],"in":[4,34,48,151,163],"medical":[5],"image":[6],"analysis,":[7],"aiding":[8],"tasks":[9],"like":[10],"surgical":[11],"navigation,":[12],"diagnosis,":[13],"and":[14,29,45,56,73,95,101,108,138,171,180],"treatment":[15],"planning.":[16],"However,":[17],"it":[18],"remains":[19],"challenging":[20,152],"due":[21],"to":[22,41,144],"the":[23,112],"need":[24],"for":[25,69,79,178],"fine-grained":[26],"local":[27,70,109],"detail":[28],"long-range":[30,93],"spatial":[31],"dependency":[32],"modeling":[33],"high-dimensional":[35],"volumetric":[36,83],"data.":[37],"Existing":[38],"approaches":[39],"struggle":[40],"balance":[42],"accuracy,":[43],"efficiency,":[44],"robustness,":[46],"especially":[47],"cases":[49],"of":[50,114],"sparse":[51],"landmark":[52],"distribution,":[53],"anatomical":[54,158],"variability,":[55],"noisy":[57],"or":[58,116,157],"incomplete":[59],"scans.":[60],"We":[61],"propose":[62],"H3DE-Net,":[63],"a":[64,74,122],"hybrid":[65],"framework":[66],"combining":[67],"CNNs":[68],"feature":[71,97],"extraction":[72],"lightweight":[75],"transformer-based":[76],"attention":[77,86],"module":[78],"global":[80,107],"context.":[81],"A":[82],"bi-level":[84],"routing":[85],"mechanism":[87],"reduces":[88],"computational":[89],"overhead":[90],"while":[91],"preserving":[92],"dependencies,":[94],"multi-scale":[96],"fusion":[98],"enhances":[99],"precision":[100],"robustness.":[102],"This":[103],"design":[104],"integrates":[105],"both":[106],"representations,":[110],"overcoming":[111],"limitations":[113],"CNN-only":[115],"transformer-only":[117],"models.":[118],"Extensive":[119],"experiments":[120],"on":[121],"public":[123],"CT":[124],"dataset":[125],"show":[126],"that":[127],"H3DE-Net":[128],"achieves":[129],"state-of-the-art":[130],"performance,":[131],"significantly":[132],"improving":[133],"mean":[134],"radial":[135],"error":[136],"(MRE)":[137],"success":[139],"rate":[141],"(SDR)":[142],"compared":[143],"existing":[145],"methods.":[146],"The":[147],"model":[148],"robust":[150],"scenarios":[153],"with":[154],"missing":[155],"landmarks":[156],"variations,":[159],"demonstrating":[160],"its":[161],"applicability":[162],"real-world":[164],"clinical":[165],"settings.":[166],"All":[167],"code,":[168],"pretrained":[169],"weights,":[170],"data":[172],"processing":[173],"scripts":[174],"are":[175],"publicly":[176],"available":[177],"reproducibility":[179],"further":[181],"research.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2026-01-30T00:00:00"}
