{"id":"https://openalex.org/W7126110955","doi":"https://doi.org/10.1109/bibm66473.2025.11357151","title":"Cross-Jrs: Bidirectional-Enhancement Framework with Domain Fusion for Multimodal Joint Registration and Segmentation","display_name":"Cross-Jrs: Bidirectional-Enhancement Framework with Domain Fusion for Multimodal Joint Registration and Segmentation","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126110955","doi":"https://doi.org/10.1109/bibm66473.2025.11357151"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11357151","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357151","pdf_url":null,"source":null,"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"},"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":"https://openalex.org/A5102696762","display_name":"Yulong Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yulong Guo","raw_affiliation_strings":["Southern University of Science and Technology,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology,Shenzhen,China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101641385","display_name":"Libin Chen","orcid":"https://orcid.org/0000-0002-4035-0828"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Chen","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022441060","display_name":"Qingqing Zheng","orcid":"https://orcid.org/0000-0001-7726-1901"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingqing Zheng","raw_affiliation_strings":["Shenzhen University of Advanced Technology,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University of Advanced Technology,Shenzhen,China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124153662","display_name":"Qiong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiong Wang","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China","institution_ids":["https://openalex.org/I4210145761"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102696762"],"corresponding_institution_ids":["https://openalex.org/I3045169105"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.69256863,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3634","last_page":"3639"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.39570000767707825,"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"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.39570000767707825,"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":0.38960000872612,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.053599998354911804,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7849000096321106},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5827999711036682},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5327000021934509},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5307999849319458},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.49470001459121704},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4708000123500824},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.43130001425743103},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4043000042438507}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8027999997138977},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7849000096321106},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.72079998254776},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6115000247955322},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5827999711036682},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5327000021934509},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5307999849319458},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.49470001459121704},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4708000123500824},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.43130001425743103},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4043000042438507},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.40369999408721924},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39879998564720154},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.37599998712539673},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.35499998927116394},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3481999933719635},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C2780910867","wikidata":"https://www.wikidata.org/wiki/Q1952416","display_name":"Multimodality","level":2,"score":0.30970001220703125},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.30730000138282776},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.28290000557899475},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11357151","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357151","pdf_url":null,"source":null,"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"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41904279589653015,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G908830822","display_name":null,"funder_award_id":"U23A20391","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2816936748","https://openalex.org/W2891631795","https://openalex.org/W2918257301","https://openalex.org/W2979378912","https://openalex.org/W2979457045","https://openalex.org/W3180275357","https://openalex.org/W3202591199","https://openalex.org/W4213089245","https://openalex.org/W4383500910","https://openalex.org/W4387143917","https://openalex.org/W4387225507","https://openalex.org/W4387225959","https://openalex.org/W4391582541","https://openalex.org/W4399310779","https://openalex.org/W4399401304","https://openalex.org/W4402715997","https://openalex.org/W4404212754","https://openalex.org/W4405978172","https://openalex.org/W4406260699"],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"medical":[1],"image":[2],"registration":[3,15,88,149],"critically":[4],"relies":[5],"on":[6,130],"anatomical":[7],"guidance":[8],"for":[9,34,147],"accurate":[10],"spatial":[11,102],"alignment.":[12],"However,":[13],"existing":[14],"approaches":[16],"fail":[17],"to":[18],"fully":[19],"exploit":[20],"the":[21,70,91,110,139,143],"potential":[22],"of":[23,69],"segmentation":[24,85,98,151],"labels,":[25],"while":[26,90],"joint":[27],"registrationsegmentation":[28],"(JRS)":[29],"frameworks":[30],"lack":[31],"effective":[32],"mechanisms":[33],"bidirectional":[35,71],"task":[36],"co-enhancement.":[37],"To":[38,104],"address":[39],"these":[40],"challenges,":[41],"we":[42],"propose":[43],"CROSS-JRS,":[44],"a":[45,66],"novel":[46],"framework":[47],"that":[48,138],"achieves":[49],"mutual":[50],"reinforcement":[51],"between":[52],"both":[53,148],"tasks":[54],"through":[55,100],"synergistic":[56,62],"innovations.":[57],"Specifically,":[58],"CROSS-JRS":[59,141],"comprises":[60],"three":[61],"modules,":[63],"each":[64],"targeting":[65],"key":[67],"aspect":[68],"interaction:":[72],"The":[73,153],"Segmentation-Guided":[74],"Local-Global":[75],"(SGLG)":[76],"module":[77,95,115],"hierarchically":[78],"estimates":[79],"deformations":[80],"by":[81],"progressively":[82],"integrating":[83],"multi-scale":[84],"features":[86,106,120],"with":[87],"cues,":[89],"Registration-Assisted":[92],"Cross-Enhancement":[93],"(RACE)":[94],"reciprocally":[96],"improves":[97],"accuracy":[99],"registrationderived":[101],"correspondences.":[103],"bridge":[105],"from":[107],"complementary":[108],"tasks,":[109],"Dual-Attention":[111],"Domain":[112],"Fusion":[113],"(DADF)":[114],"aligns":[116],"and":[117,150],"fuses":[118],"cross-task":[119],"via":[121],"dynamic":[122],"attention":[123],"gating,":[124],"enabling":[125],"feature-level":[126],"co-adaptation.":[127],"Extensive":[128],"experiments":[129],"two":[131],"public":[132],"3D":[133],"prostate":[134],"MRI-US":[135],"datasets":[136],"demonstrate":[137],"proposed":[140],"outperforms":[142],"state-of-the-art":[144],"JRS":[145],"methods":[146],"tasks.":[152],"code":[154],"is":[155],"available":[156],"at":[157],"https://github.com/scuterGuoyulong/CROSS-JRS.":[158]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-30T00:00:00"}