{"id":"https://openalex.org/W7126041780","doi":"https://doi.org/10.1109/bibm66473.2025.11356991","title":"Beyond Probability Guided Categorization: A Subspace Projection-Aware Approach for Medical Image Segmentation","display_name":"Beyond Probability Guided Categorization: A Subspace Projection-Aware Approach for Medical Image Segmentation","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126041780","doi":"https://doi.org/10.1109/bibm66473.2025.11356991"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356991","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356991","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":"conference-paper","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/A5066788312","display_name":"Xiao Luan","orcid":"https://orcid.org/0000-0003-0010-7361"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Luan","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications,Chongqing Key Laboratory of Image Cognition,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications,Chongqing Key Laboratory of Image Cognition,Chongqing,China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111058143","display_name":"Yule Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yule Fu","raw_affiliation_strings":["School of Computer Science and Technology, Chongqing University of Posts and Telecommunications,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications,Chongqing,China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018691364","display_name":"Linghui Liu","orcid":"https://orcid.org/0000-0001-5833-6146"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linghui Liu","raw_affiliation_strings":["School of Computer Science and Technology, Chongqing University of Posts and Telecommunications,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications,Chongqing,China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092025072","display_name":"Chen Li","orcid":"https://orcid.org/0000-0002-0290-2046"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Li","raw_affiliation_strings":["School of Computer Science and Technology, Chongqing University of Posts and Telecommunications,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications,Chongqing,China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124283472","display_name":"Weisheng Li","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weisheng Li","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications,Chongqing Key Laboratory of Image Cognition,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications,Chongqing Key Laboratory of Image Cognition,Chongqing,China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I10535382"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.61379374,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4279","last_page":"4282"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.5421000123023987,"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":0.5421000123023987,"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":0.2538999915122986,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.014299999922513962,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.9035999774932861},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7475000023841858},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7222999930381775},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6913999915122986},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6452999711036682},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.605400025844574},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.5087000131607056},{"id":"https://openalex.org/keywords/orthogonality","display_name":"Orthogonality","score":0.49399998784065247}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9035999774932861},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7475000023841858},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7222999930381775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6969000101089478},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6913999915122986},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6452999711036682},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.605400025844574},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.5087000131607056},{"id":"https://openalex.org/C17137986","wikidata":"https://www.wikidata.org/wiki/Q215067","display_name":"Orthogonality","level":2,"score":0.49399998784065247},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.491100013256073},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.49070000648498535},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.46970000863075256},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.41670000553131104},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38119998574256897},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.36959999799728394},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3628000020980835},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.34119999408721924},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2928999960422516},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2547000050544739},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356991","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356991","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":[{"id":"https://metadata.un.org/sdg/10","score":0.7493711709976196,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2640149350","display_name":null,"funder_award_id":"cstc2022ycjhbgzxm0004","funder_id":"https://openalex.org/F4320323172","funder_display_name":"Natural Science Foundation of Chongqing"},{"id":"https://openalex.org/G5595033988","display_name":null,"funder_award_id":"62276041,62331008,62136002","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"},{"id":"https://openalex.org/F4320323172","display_name":"Natural Science Foundation of Chongqing","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2295107390","https://openalex.org/W2464708700","https://openalex.org/W2765793020","https://openalex.org/W2962858109","https://openalex.org/W2962914239","https://openalex.org/W2963046541","https://openalex.org/W3014974815","https://openalex.org/W3035253074","https://openalex.org/W3202988816","https://openalex.org/W3203841574","https://openalex.org/W4212875960","https://openalex.org/W4221163766","https://openalex.org/W4296123084","https://openalex.org/W4386065251","https://openalex.org/W4387211619","https://openalex.org/W4402702948","https://openalex.org/W4403066998","https://openalex.org/W4415798061"],"related_works":[],"abstract_inverted_index":{"Most":[0],"current":[1],"medical":[2],"image":[3],"segmentation":[4,21,38,221],"(MIS)":[5],"methods":[6],"focus":[7],"on":[8,158,198],"the":[9,15,23,28,35,48,51,55,64,69,85,95,113,127,141,159,169,186,190,224],"performance":[10,86],"of":[11,17,25,27,37,42,89,98,116,130,219,226],"models":[12,100,202,216],"while":[13],"overlooking":[14],"interpretability":[16,88,225],"models.":[18,91],"For":[19],"existing":[20],"models,":[22],"number":[24,36],"channels":[26],"output":[29,96],"feature":[30,120,131,146,166,180],"maps":[31],"is":[32,45,137,196],"equal":[33],"to":[34,82,122,139,177],"categories.":[39],"The":[40],"category":[41,71,151,171],"each":[43,117],"pixel":[44,118,154],"determined":[46,156],"by":[47,63],"channel":[49,114],"with":[50,101,153],"highest":[52],"probability,":[53],"yet":[54],"reasons":[56],"for":[57],"this":[58],"decision":[59],"are":[60,72,148,173],"unclear.":[61],"Inspired":[62],"principle":[65],"that":[66,106,165,211],"samples":[67],"from":[68],"same":[70,170],"spatially":[73],"closer,":[74],"we":[75,184],"propose":[76],"a":[77,102],"novel":[78],"subspace":[79,172,191],"projection":[80,161],"method":[81,195],"enhance":[83],"both":[84,220],"and":[87,111,176,189,223],"MIS":[90,201],"Our":[92,194],"approach":[93,213],"replaces":[94],"layer":[97,105],"baseline":[99,215],"new":[103],"convolutional":[104],"enhances":[107],"channel-wise":[108],"representational":[109],"power,":[110],"concatenates":[112],"features":[115],"into":[119,150],"vectors":[121,147,167],"integrate":[123],"channel-level":[124],"information.":[125],"Considering":[126],"sparse":[128],"structure":[129],"vectors,":[132],"an":[133],"overcomplete":[134],"dictionary":[135],"learning":[136,181],"applied":[138],"extract":[140],"most":[142],"discriminative":[143],"features.":[144],"These":[145],"projected":[149],"subspaces,":[152,183],"classification":[155],"based":[157],"smallest":[160],"distance.":[162],"To":[163],"guarantee":[164],"within":[168],"grouped":[174],"closely":[175],"promote":[178],"nonoverlapping":[179],"across":[182],"introduce":[185],"distance":[187],"loss":[188],"orthogonality":[192],"loss.":[193],"evaluated":[197],"ten":[199],"popular":[200],"using":[203],"two":[204],"publicly":[205],"available":[206],"datasets.":[207],"Experimental":[208],"results":[209],"show":[210],"our":[212],"outperforms":[214],"in":[217],"terms":[218],"accuracy":[222],"model":[227],"decision.":[228]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-01-30T00:00:00"}