{"id":"https://openalex.org/W7166133138","doi":"https://doi.org/10.1109/access.2026.3707636","title":"Cross-Slice Transformer With Adaptive Slice Fusion for Lymph Node Segmentation in CT Imaging","display_name":"Cross-Slice Transformer With Adaptive Slice Fusion for Lymph Node Segmentation in CT Imaging","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166133138","doi":"https://doi.org/10.1109/access.2026.3707636"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3707636","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3707636","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.2026.3707636","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053252802","display_name":"Beibit Abdikenov","orcid":"https://orcid.org/0000-0002-0284-0949"},"institutions":[{"id":"https://openalex.org/I4210141757","display_name":"Astana Medical University","ror":"https://ror.org/038mavt60","country_code":"KZ","type":"education","lineage":["https://openalex.org/I4210141757"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Beibit Abdikenov","raw_affiliation_strings":["Science and Innovation Center &#x201C;Artificial Intelligence,&#x201D; Astana IT University, Astana, Kazakhstan"],"raw_orcid":"https://orcid.org/0000-0002-0284-0949","affiliations":[{"raw_affiliation_string":"Science and Innovation Center &#x201C;Artificial Intelligence,&#x201D; Astana IT University, Astana, Kazakhstan","institution_ids":["https://openalex.org/I4210141757"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139405794","display_name":"Zhaidar Kairat","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141757","display_name":"Astana Medical University","ror":"https://ror.org/038mavt60","country_code":"KZ","type":"education","lineage":["https://openalex.org/I4210141757"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Zhaidar Kairat","raw_affiliation_strings":["Science and Innovation Center &#x201C;Artificial Intelligence,&#x201D; Astana IT University, Astana, Kazakhstan"],"raw_orcid":"https://orcid.org/0009-0001-5151-6846","affiliations":[{"raw_affiliation_string":"Science and Innovation Center &#x201C;Artificial Intelligence,&#x201D; Astana IT University, Astana, Kazakhstan","institution_ids":["https://openalex.org/I4210141757"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133616232","display_name":"Tomiris M. Zhaksylyk","orcid":"https://orcid.org/0009-0002-8749-1967"},"institutions":[{"id":"https://openalex.org/I4210141757","display_name":"Astana Medical University","ror":"https://ror.org/038mavt60","country_code":"KZ","type":"education","lineage":["https://openalex.org/I4210141757"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Tomiris Zhaksylyk","raw_affiliation_strings":["Science and Innovation Center &#x201C;Artificial Intelligence,&#x201D; Astana IT University, Astana, Kazakhstan"],"raw_orcid":"https://orcid.org/0009-0002-8749-1967","affiliations":[{"raw_affiliation_string":"Science and Innovation Center &#x201C;Artificial Intelligence,&#x201D; Astana IT University, Astana, Kazakhstan","institution_ids":["https://openalex.org/I4210141757"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011819162","display_name":"Yerzhan Orazayev","orcid":"https://orcid.org/0009-0004-9826-625X"},"institutions":[{"id":"https://openalex.org/I4210141757","display_name":"Astana Medical University","ror":"https://ror.org/038mavt60","country_code":"KZ","type":"education","lineage":["https://openalex.org/I4210141757"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Yerzhan Orazayev","raw_affiliation_strings":["Science and Innovation Center &#x201C;Artificial Intelligence,&#x201D; Astana IT University, Astana, Kazakhstan"],"raw_orcid":"https://orcid.org/0009-0004-9826-625X","affiliations":[{"raw_affiliation_string":"Science and Innovation Center &#x201C;Artificial Intelligence,&#x201D; Astana IT University, Astana, Kazakhstan","institution_ids":["https://openalex.org/I4210141757"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032890791","display_name":"Birzhan Ayanbayev","orcid":"https://orcid.org/0000-0002-0925-4045"},"institutions":[{"id":"https://openalex.org/I4210141757","display_name":"Astana Medical University","ror":"https://ror.org/038mavt60","country_code":"KZ","type":"education","lineage":["https://openalex.org/I4210141757"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Birzhan Ayanbayev","raw_affiliation_strings":["Science and Innovation Center &#x201C;Artificial Intelligence,&#x201D; Astana IT University, Astana, Kazakhstan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Innovation Center &#x201C;Artificial Intelligence,&#x201D; Astana IT University, Astana, Kazakhstan","institution_ids":["https://openalex.org/I4210141757"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121635182","display_name":"Nurbek Saidnassim","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141757","display_name":"Astana Medical University","ror":"https://ror.org/038mavt60","country_code":"KZ","type":"education","lineage":["https://openalex.org/I4210141757"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Nurbek Saidnassim","raw_affiliation_strings":["Science and Innovation Center &#x201C;Artificial Intelligence,&#x201D; Astana IT University, Astana, Kazakhstan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Innovation Center &#x201C;Artificial Intelligence,&#x201D; Astana IT University, Astana, Kazakhstan","institution_ids":["https://openalex.org/I4210141757"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210141757"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.78504957,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"98650","last_page":"98666"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.527400016784668,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.527400016784668,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.07660000026226044,"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/T11363","display_name":"Dental Radiography and Imaging","score":0.07479999959468842,"subfield":{"id":"https://openalex.org/subfields/3504","display_name":"Oral Surgery"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6269999742507935},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.604200005531311},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4408000111579895},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.38960000872612},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.3458999991416931},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3418000042438507}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6470999717712402},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6269999742507935},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.604200005531311},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5861999988555908},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5703999996185303},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4408000111579895},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.38960000872612},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.3458999991416931},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3418000042438507},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3034000098705292},{"id":"https://openalex.org/C2780849966","wikidata":"https://www.wikidata.org/wiki/Q170758","display_name":"Lymph node","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C160671074","wikidata":"https://www.wikidata.org/wiki/Q267131","display_name":"Wafer","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.25450000166893005}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3707636","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3707636","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:505893640f88417e911771f141683bee","is_oa":false,"landing_page_url":"https://doaj.org/article/505893640f88417e911771f141683bee","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 98650-98666 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3707636","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3707636","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/G7666425260","display_name":null,"funder_award_id":"BR24993145","funder_id":"https://openalex.org/F4320322726","funder_display_name":"Ministry of Education and Science of the Republic of Kazakhstan"}],"funders":[{"id":"https://openalex.org/F4320322726","display_name":"Ministry of Education and Science of the Republic of Kazakhstan","ror":"https://ror.org/03pj6ge82"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"lymph":[1,344],"node":[2,23,345],"assessment":[3],"on":[4,82,110,114,222,229,262],"computed":[5],"tomography":[6],"(CT)":[7],"is":[8,68,281],"essential":[9],"for":[10,232,238,243,335],"cancer":[11],"staging":[12],"and":[13,28,59,77,95,97,138,177,202,241,320,339],"treatment":[14],"planning,":[15],"yet":[16],"automation":[17],"remains":[18,121],"challenging":[19],"due":[20],"to":[21,192,275],"small":[22,233],"size,":[24],"low":[25],"soft-tissue":[26],"contrast,":[27],"extreme":[29],"class":[30],"imbalance":[31],"(foreground":[32],"voxels":[33],"comprising":[34],"below":[35],"1%":[36],"of":[37,181,196,270,285,297],"the":[38,42,78,106,122,152,165,187,194,295,311],"volume).":[39],"We":[40],"propose":[41],"Cross-Slice":[43],"Transformer":[44],"(CST),":[45],"a":[46,88,98,142,178,282,317],"lightweight":[47],"2.5D":[48,72,135,156,169,188,336],"architecture":[49,337],"that":[50,117,215,278],"learns":[51],"adaptive":[52,301],"slice":[53],"importance":[54],"through":[55],"statistical":[56],"descriptor":[57,313],"extraction":[58],"transformer-based":[60],"attention":[61,303],"over":[62,307,316,326],"five":[63],"consecutive":[64],"CT":[65],"slices.":[66],"CST":[67,150,197,216,299],"evaluated":[69],"against":[70],"three":[71],"baselines":[73,189],"(U-Net,":[74],"TransUNet,":[75],"SwinUNet)":[76],"3D":[79,144],"nnUNet":[80],"framework":[81],"two":[83],"publicly":[84],"available":[85],"TCIA":[86],"datasets:":[87],"multi-region":[89],"dataset":[90,100,139,279,340],"(Ver1,":[91],"296":[92],"patients,":[93],"mediastinal":[94],"abdominal)":[96],"mediastinal-focused":[99],"(Ver2,":[101],"206":[102],"patients).":[103],"nnUNet-3D":[104,221],"achieves":[105,151],"highest":[107,153,166],"overall":[108,209],"Dice":[109,154,268,306],"both":[111],"datasets":[112],"(0.589":[113],"Ver2),":[115],"confirming":[116],"full":[118],"volumetric":[119],"context":[120],"strongest":[123],"approach":[124],"when":[125,260],"GPU":[126],"resources":[127],"permit.":[128],"Our":[129],"central":[130],"research":[131],"questions":[132],"instead":[133],"concern":[134],"architectural":[136,290],"design":[137],"composition,":[140],"which":[141],"single":[143],"model":[145],"cannot":[146],"address.":[147],"On":[148],"Ver2,":[149,276],"among":[155,168],"models":[157,170,219,257],"(<inline-formula>":[158,171,245],"<tex-math":[159,172,246,252],"notation=\"LaTeX\">$0.543":[160],"\\pm":[161,174],"0.044$":[162],"</tex-math></inline-formula>),":[163],"with":[164,267],"recall":[167],"notation=\"LaTeX\">$0.618":[173],"0.024$":[175],"</tex-math></inline-formula>)":[176],"compact":[179],"footprint":[180],"7.97&#x2006;M":[182],"parameters,":[183],"substantially":[184],"fewer":[185],"than":[186,207],"(25&#x2013;99&#x2006;M).":[190],"Relative":[191],"nnUNet-3D,":[193],"advantages":[195],"lie":[198],"in":[199,203,208,342],"this":[200],"compactness":[201],"node-level":[204],"detection":[205,212,223],"rather":[206],"Dice.":[210],"Node-level":[211],"analysis":[213],"reveals":[214],"leads":[217],"all":[218,226,289],"including":[220],"rate":[224],"across":[225,288],"size":[227],"strata":[228],"Ver2:":[230],"53.6%":[231],"nodes":[234],"(&#x003C;":[235],"10&#x2006;mm),":[236],"82.9%":[237],"medium":[239],"(10&#x2013;15&#x2006;mm),":[240],"92.5%":[242],"large":[244],"notation=\"LaTeX\">$\\geq":[247,253],"15$":[248],"</tex-math></inline-formula>&#x2006;mm)":[249],"at":[250],"IoU&#x2006;<inline-formula>":[251],"$":[254],"</tex-math></inline-formula>&#x2006;0.1.":[255],"All":[256],"improve":[258],"consistently":[259],"trained":[261],"anatomically":[263],"focused":[264],"single-region":[265],"data,":[266],"gains":[269],"0.047&#x2013;0.152":[271],"points":[272],"from":[273],"Ver1":[274],"demonstrating":[277],"composition":[280],"primary":[283],"driver":[284],"segmentation":[286],"performance":[287],"families.":[291],"Ablation":[292],"experiments":[293],"confirm":[294],"contribution":[296],"each":[298],"component:":[300],"transformer":[302],"(+":[304,314,324],"0.006":[305],"fixed":[308,327],"uniform":[309],"weights),":[310],"interaction":[312],"0.008":[315,325],"reduced":[318],"descriptor),":[319],"per-case":[321],"intensity":[322],"normalisation":[323],"HU":[328],"windowing).":[329],"These":[330],"results":[331],"provide":[332],"evidence-based":[333],"guidance":[334],"selection":[338],"curation":[341],"clinical":[343],"segmentation.":[346]},"counts_by_year":[],"updated_date":"2026-07-04T06:09:54.619538","created_date":"2026-06-27T00:00:00"}