{"id":"https://openalex.org/W7137958042","doi":"https://doi.org/10.1609/aaai.v40i14.38186","title":"Conformable Convolution for Topologically Constrained Learning of Complex Anatomical Structures","display_name":"Conformable Convolution for Topologically Constrained Learning of Complex Anatomical Structures","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7137958042","doi":"https://doi.org/10.1609/aaai.v40i14.38186"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i14.38186","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i14.38186","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i14.38186","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129698207","display_name":"Yousef Yeganeh","orcid":null},"institutions":[{"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":"Yousef Yeganeh","raw_affiliation_strings":["Technical University of Munich\nMunich Center for Machine Learning"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Munich\nMunich Center for Machine Learning","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129660892","display_name":"Goktug Guvercin","orcid":null},"institutions":[{"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":"Goktug Guvercin","raw_affiliation_strings":["Technical University of Munich"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Munich","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129678610","display_name":"Nassir Navab","orcid":null},"institutions":[{"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":"Nassir Navab","raw_affiliation_strings":["Technical University of Munich\nMunich Center for Machine Learning\nELLIS Unit Munich"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Munich\nMunich Center for Machine Learning\nELLIS Unit Munich","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014777005","display_name":"Azade Farshad","orcid":"https://orcid.org/0000-0002-1080-1587"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Azade Farshad","raw_affiliation_strings":["ELLIS Institute Finland\nAalto University\nTechnical University of Munich\nMunich Center for Machine Learning"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ELLIS Institute Finland\nAalto University\nTechnical University of Munich\nMunich Center for Machine Learning","institution_ids":["https://openalex.org/I9927081"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"14","first_page":"11982","last_page":"11990"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.00279999990016222,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12923","display_name":"Digital Image Processing Techniques","score":0.0010000000474974513,"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/topological-data-analysis","display_name":"Topological data analysis","score":0.6809999942779541},{"id":"https://openalex.org/keywords/conformable-matrix","display_name":"Conformable matrix","score":0.6363000273704529},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.5997999906539917},{"id":"https://openalex.org/keywords/persistent-homology","display_name":"Persistent homology","score":0.5557000041007996},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5181999802589417},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4742000102996826},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.43790000677108765},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.42890000343322754},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.42719998955726624}],"concepts":[{"id":"https://openalex.org/C2776477805","wikidata":"https://www.wikidata.org/wiki/Q4460773","display_name":"Topological data analysis","level":2,"score":0.6809999942779541},{"id":"https://openalex.org/C86072612","wikidata":"https://www.wikidata.org/wiki/Q5160239","display_name":"Conformable matrix","level":2,"score":0.6363000273704529},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6171000003814697},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.5997999906539917},{"id":"https://openalex.org/C2874115","wikidata":"https://www.wikidata.org/wiki/Q17099562","display_name":"Persistent homology","level":2,"score":0.5557000041007996},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5181999802589417},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4742000102996826},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46700000762939453},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.43790000677108765},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.42890000343322754},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.42719998955726624},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4171000123023987},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.40220001339912415},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.3946000039577484},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3262999951839447},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.3197999894618988},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.31189998984336853},{"id":"https://openalex.org/C165525559","wikidata":"https://www.wikidata.org/wiki/Q224180","display_name":"Homology (biology)","level":3,"score":0.28279998898506165},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C165263651","wikidata":"https://www.wikidata.org/wiki/Q2443460","display_name":"Topological conjugacy","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25690001249313354},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25099998712539673}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i14.38186","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i14.38186","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/38186","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/38186","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i14.38186","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i14.38186","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"While":[0],"conventional":[1],"computer":[2],"vision":[3],"emphasizes":[4],"pixel-level":[5],"and":[6,37,113,198],"feature-based":[7],"objectives,":[8],"medical":[9],"image":[10],"analysis":[11],"of":[12,19,39,83,136,167,178],"intricate":[13],"biological":[14],"structures":[15,45,179],"necessitates":[16],"explicit":[17],"representation":[18],"their":[20,25,48],"complex":[21],"topological":[22,71,85,111,147],"properties.":[23],"Despite":[24],"successes,":[26],"deep":[27],"learning":[28,52,143],"models":[29],"often":[30],"struggle":[31],"to":[32,47,68,122,145,156],"accurately":[33],"capture":[34],"the":[35,115,142,165,171,176,194],"connectivity":[36],"continuity":[38],"fine,":[40],"sometimes":[41],"pixel-thin,":[42],"yet":[43],"critical":[44],"due":[46],"reliance":[49],"on":[50,81,184],"implicit":[51],"from":[53],"data.":[54],"To":[55],"address":[56],"this":[57],"challenge,":[58],"we":[59],"introduce":[60],"Conformable":[61,73],"Convolution,":[62],"a":[63],"novel":[64],"convolutional":[65,116],"layer":[66],"designed":[67],"explicitly":[69,140],"impose":[70],"consistency.":[72],"Convolution":[74],"learns":[75],"adaptive":[76],"kernel":[77],"offsets":[78],"that":[79,132,189],"focus":[80],"regions":[82],"high":[84],"significance":[86],"within":[87],"an":[88],"image.":[89],"This":[90],"prioritization":[91],"is":[92,180],"guided":[93],"by":[94,118],"our":[95,138,168,190],"proposed":[96,150],"Topological":[97],"Posterior":[98],"Generator":[99],"(TPG)":[100],"module,":[101],"which":[102],"leverages":[103],"persistent":[104,120],"homology.":[105],"The":[106,149,182],"TPG":[107],"module":[108],"identifies":[109],"key":[110],"features":[112],"guides":[114],"layers":[117],"applying":[119],"homology":[121],"feature":[123],"maps":[124],"transformed":[125],"into":[126,160],"cubical":[127],"complexes.":[128],"Unlike":[129],"existing":[130],"approaches":[131],"are":[133,152],"merely":[134],"aware":[135],"topology,":[137],"method":[139],"constrains":[141],"process":[144],"ensure":[146],"correctness.":[148],"modules":[151],"architecture-agnostic,":[153],"enabling":[154],"them":[155],"be":[157],"integrated":[158],"seamlessly":[159],"various":[161],"architectures.":[162],"We":[163],"showcase":[164],"effectiveness":[166],"framework":[169,191],"in":[170],"segmentation":[172],"task,":[173],"where":[174],"preserving":[175],"interconnectedness":[177],"critical.":[181],"results":[183],"three":[185],"diverse":[186],"datasets":[187],"demonstrate":[188],"effectively":[192],"preserves":[193],"topology":[195],"both":[196],"quantitatively":[197],"qualitatively.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-18T00:00:00"}
