{"id":"https://openalex.org/W7154266896","doi":"https://doi.org/10.1016/j.array.2026.100826","title":"SpAw: A spatially-aware self-supervised framework for 3D medical image segmentation","display_name":"SpAw: A spatially-aware self-supervised framework for 3D medical image segmentation","publication_year":2026,"publication_date":"2026-04-14","ids":{"openalex":"https://openalex.org/W7154266896","doi":"https://doi.org/10.1016/j.array.2026.100826"},"language":"en","primary_location":{"id":"doi:10.1016/j.array.2026.100826","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.array.2026.100826","pdf_url":null,"source":{"id":"https://openalex.org/S4210194039","display_name":"Array","issn_l":"2590-0056","issn":["2590-0056"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Array","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1016/j.array.2026.100826","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053935189","display_name":"Bin Zhang","orcid":"https://orcid.org/0000-0002-5976-2806"},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Zhang","raw_affiliation_strings":["School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, 541004, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, 541004, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123849269","display_name":"Zhichao Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhichao Ma","raw_affiliation_strings":["School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, 541004, China"],"raw_orcid":"https://orcid.org/0009-0008-7268-5375","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, 541004, China","institution_ids":["https://openalex.org/I5343935"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5123849269"],"corresponding_institution_ids":["https://openalex.org/I5343935"],"apc_list":{"value":1350,"currency":"USD","value_usd":1350},"apc_paid":{"value":1350,"currency":"USD","value_usd":1350},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.49906563,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":null,"first_page":"100826","last_page":"100826"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.29350000619888306,"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":0.29350000619888306,"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":0.21649999916553497,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.04670000076293945,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/image-segmentation","display_name":"Image segmentation","score":0.49900001287460327},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.460099995136261},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.40049999952316284},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.400299996137619},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35190001130104065},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3325999975204468}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6947000026702881},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6316999793052673},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5990999937057495},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.49900001287460327},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.460099995136261},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40049999952316284},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.400299996137619},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35190001130104065},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3325999975204468},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.28029999136924744},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2800000011920929}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.array.2026.100826","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.array.2026.100826","pdf_url":null,"source":{"id":"https://openalex.org/S4210194039","display_name":"Array","issn_l":"2590-0056","issn":["2590-0056"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Array","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.array.2026.100826","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.array.2026.100826","pdf_url":null,"source":{"id":"https://openalex.org/S4210194039","display_name":"Array","issn_l":"2590-0056","issn":["2590-0056"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Array","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7163800938","display_name":null,"funder_award_id":"62361013","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2533800772","https://openalex.org/W2584017349","https://openalex.org/W2883725317","https://openalex.org/W2995848654","https://openalex.org/W3138516171","https://openalex.org/W3145450063","https://openalex.org/W3159481202","https://openalex.org/W3172615411","https://openalex.org/W4313156423","https://openalex.org/W4319300504","https://openalex.org/W4327769487","https://openalex.org/W4367355047","https://openalex.org/W4377235500","https://openalex.org/W4377819235","https://openalex.org/W4386076174","https://openalex.org/W4386076446","https://openalex.org/W4386076598","https://openalex.org/W4387211540","https://openalex.org/W4387211595","https://openalex.org/W4401211295","https://openalex.org/W4402703096","https://openalex.org/W4406075583","https://openalex.org/W4409014564","https://openalex.org/W4410359301"],"related_works":[],"abstract_inverted_index":{"In":[0],"3D":[1,18,54,213],"medical":[2],"image":[3],"segmentation,":[4],"high-quality":[5],"annotations":[6],"are":[7],"scarce":[8],"and":[9,27,75,92,115,172,197,202,211,232],"costly.":[10],"Existing":[11],"self-supervised":[12,37,183,223],"learning":[13],"methods":[14],"often":[15],"overlook":[16],"intrinsic":[17],"spatial":[19,73,214],"structural":[20],"priors,":[21,215],"yielding":[22],"representations":[23],"lacking":[24],"anatomical":[25,219],"semantics":[26],"struggling":[28],"with":[29,229],"fine-grained":[30],"segmentation.":[31],"We":[32,156],"propose":[33],"SpAw,":[34],"a":[35,45,59,71,85,93,122],"spatially-aware":[36,123],"framework":[38],"featuring":[39],"two":[40,106],"geometrically":[41],"interpretable":[42],"pretext":[43],"tasks:":[44],"global":[46,210],"absolute":[47],"position":[48,96,104],"prediction":[49,97],"task,":[50,98],"in":[51,222],"which":[52,99],"the":[53,76,82,102,129,136],"volume":[55],"is":[56,78],"partitioned":[57],"into":[58],"4":[60,62],"\u00d7":[61,63],"2":[64],"grid":[65],"of":[66,84,191],"anchor":[67],"patches,":[68],"each":[69],"representing":[70],"distinct":[72],"category,":[74],"model":[77],"trained":[79],"to":[80],"predict":[81],"location":[83],"randomly":[86],"cropped":[87,108],"patch":[88,140],"using":[89],"soft":[90],"labels;":[91],"local":[94,212],"relative":[95,103],"jointly":[100],"estimates":[101],"between":[105,139],"overlapping":[107],"patches":[109],"through":[110],"an":[111],"attention-based":[112],"MLP":[113],"regressor":[114],"similarity-weighted":[116],"geometric":[117],"inference.":[118],"Furthermore,":[119],"we":[120],"incorporate":[121],"discrepancy":[124,144],"regularization":[125],"that":[126],"dynamically":[127],"modulates":[128],"penalty":[130],"on":[131,135,159,193,200,204],"feature":[132,143],"similarity":[133],"based":[134],"Euclidean":[137],"distance":[138],"pairs,":[141],"encouraging":[142],"for":[145],"distant":[146],"regions":[147],"while":[148],"preserving":[149],"semantic":[150,220],"consistency":[151],"among":[152],"spatially":[153],"proximal":[154],"neighbors.":[155],"evaluate":[157],"SpAw":[158,178,216],"three":[160],"public,":[161],"multi-modal,":[162],"multi-anatomical":[163],"benchmark":[164],"datasets:":[165],"BTCV":[166],"(abdominal":[167],"CT),":[168],"MM-WHS":[169],"(cardiac":[170],"CT/MRI),":[171],"BraTS":[173,205],"2021":[174],"(brain":[175],"tumor":[176],"MRI).":[177],"consistently":[179],"outperforms":[180],"current":[181],"state-of-the-art":[182],"methods.":[184],"Specifically,":[185],"it":[186],"achieves":[187],"average":[188],"Dice":[189],"scores":[190],"85.06%":[192],"BTCV,":[194],"90.79%":[195],"(CT)":[196],"89.16%":[198],"(MRI)":[199],"MM-WHS,":[201],"90.82%":[203],"2021.":[206],"By":[207],"explicitly":[208],"modeling":[209],"significantly":[217],"enhances":[218],"understanding":[221],"pre-training,":[224],"producing":[225],"downstream":[226],"segmentation":[227],"features":[228],"superior":[230],"discriminability":[231],"generalizability.":[233]},"counts_by_year":[],"updated_date":"2026-06-19T17:40:00.097472","created_date":"2026-04-15T00:00:00"}
