{"id":"https://openalex.org/W7126029235","doi":"https://doi.org/10.1109/bibm66473.2025.11357071","title":"Multi-Modality MRI Semantic Segmentation via Edge-Aware Robust Principal Component Analysis","display_name":"Multi-Modality MRI Semantic Segmentation via Edge-Aware Robust Principal Component Analysis","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126029235","doi":"https://doi.org/10.1109/bibm66473.2025.11357071"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11357071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357071","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/A5056401979","display_name":"Lijun Zhao","orcid":"https://orcid.org/0000-0002-2305-1914"},"institutions":[{"id":"https://openalex.org/I4210115395","display_name":"Taiyuan Institute of Technology","ror":"https://ror.org/02d0fkx94","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115395"]},{"id":"https://openalex.org/I46305995","display_name":"Taiyuan University of Science and Technology","ror":"https://ror.org/01wcbdc92","country_code":"CN","type":"education","lineage":["https://openalex.org/I46305995"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lijun Zhao","raw_affiliation_strings":["Institute of Digital Media and Communication, Taiyuan University of Science and Technology,Taiyuan,China"],"affiliations":[{"raw_affiliation_string":"Institute of Digital Media and Communication, Taiyuan University of Science and Technology,Taiyuan,China","institution_ids":["https://openalex.org/I46305995","https://openalex.org/I4210115395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124171270","display_name":"Xiaoyu Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210115395","display_name":"Taiyuan Institute of Technology","ror":"https://ror.org/02d0fkx94","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115395"]},{"id":"https://openalex.org/I46305995","display_name":"Taiyuan University of Science and Technology","ror":"https://ror.org/01wcbdc92","country_code":"CN","type":"education","lineage":["https://openalex.org/I46305995"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Feng","raw_affiliation_strings":["Institute of Digital Media and Communication, Taiyuan University of Science and Technology,Taiyuan,China"],"affiliations":[{"raw_affiliation_string":"Institute of Digital Media and Communication, Taiyuan University of Science and Technology,Taiyuan,China","institution_ids":["https://openalex.org/I46305995","https://openalex.org/I4210115395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124276190","display_name":"Jinjing Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I135714990","display_name":"North University of China","ror":"https://ror.org/047bp1713","country_code":"CN","type":"education","lineage":["https://openalex.org/I135714990"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinjing Zhang","raw_affiliation_strings":["North University of China,Data Science and Technology,Taiyuan,China"],"affiliations":[{"raw_affiliation_string":"North University of China,Data Science and Technology,Taiyuan,China","institution_ids":["https://openalex.org/I135714990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100412917","display_name":"Lin Li","orcid":"https://orcid.org/0000-0002-9434-7800"},"institutions":[{"id":"https://openalex.org/I4210115395","display_name":"Taiyuan Institute of Technology","ror":"https://ror.org/02d0fkx94","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115395"]},{"id":"https://openalex.org/I46305995","display_name":"Taiyuan University of Science and Technology","ror":"https://ror.org/01wcbdc92","country_code":"CN","type":"education","lineage":["https://openalex.org/I46305995"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Li","raw_affiliation_strings":["Institute of Digital Media and Communication, Taiyuan University of Science and Technology,Taiyuan,China"],"affiliations":[{"raw_affiliation_string":"Institute of Digital Media and Communication, Taiyuan University of Science and Technology,Taiyuan,China","institution_ids":["https://openalex.org/I46305995","https://openalex.org/I4210115395"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ruizhen Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210115395","display_name":"Taiyuan Institute of Technology","ror":"https://ror.org/02d0fkx94","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115395"]},{"id":"https://openalex.org/I46305995","display_name":"Taiyuan University of Science and Technology","ror":"https://ror.org/01wcbdc92","country_code":"CN","type":"education","lineage":["https://openalex.org/I46305995"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruizhen Liu","raw_affiliation_strings":["Institute of Digital Media and Communication, Taiyuan University of Science and Technology,Taiyuan,China"],"affiliations":[{"raw_affiliation_string":"Institute of Digital Media and Communication, Taiyuan University of Science and Technology,Taiyuan,China","institution_ids":["https://openalex.org/I46305995","https://openalex.org/I4210115395"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5056401979"],"corresponding_institution_ids":["https://openalex.org/I4210115395","https://openalex.org/I46305995"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.84032306,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5573","last_page":"5580"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.41190001368522644,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.41190001368522644,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.1835000067949295,"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":0.0860000029206276,"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/segmentation","display_name":"Segmentation","score":0.8403000235557556},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5760999917984009},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5701000094413757},{"id":"https://openalex.org/keywords/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.5432999730110168},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.49810001254081726},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.45890000462532043},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4560000002384186},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4415999948978424}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8403000235557556},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7601000070571899},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7501000165939331},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5760999917984009},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5701000094413757},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.5432999730110168},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.49810001254081726},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.45890000462532043},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4560000002384186},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4415999948978424},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.4327999949455261},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4219000041484833},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4180999994277954},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39419999718666077},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.3828999996185303},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3788999915122986},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29420000314712524},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11357071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357071","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":[],"awards":[{"id":"https://openalex.org/G1447240253","display_name":null,"funder_award_id":"202203021222047,202303021222164","funder_id":"https://openalex.org/F4320326179","funder_display_name":"Shanxi Province Science Foundation for Youths"},{"id":"https://openalex.org/G2816734081","display_name":null,"funder_award_id":"62202323","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5767259466","display_name":null,"funder_award_id":"2024-130","funder_id":"https://openalex.org/F4320321884","funder_display_name":"Shanxi Scholarship Council 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/F4320321884","display_name":"Shanxi Scholarship Council of China","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320326179","display_name":"Shanxi Province Science Foundation for Youths","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2952378269","https://openalex.org/W2963881378","https://openalex.org/W2964227007","https://openalex.org/W2990026901","https://openalex.org/W2996290406","https://openalex.org/W2998027336","https://openalex.org/W3015788359","https://openalex.org/W3196559017","https://openalex.org/W3207346178","https://openalex.org/W4212875960","https://openalex.org/W4310064104","https://openalex.org/W4312908055","https://openalex.org/W4321232185","https://openalex.org/W4388979137","https://openalex.org/W4394597260","https://openalex.org/W4400881081","https://openalex.org/W4401749301","https://openalex.org/W4402857769","https://openalex.org/W4411715655","https://openalex.org/W4411799527","https://openalex.org/W7083295834"],"related_works":[],"abstract_inverted_index":{"Although":[0],"deep":[1],"unfolding":[2],"networks":[3,98,122],"are":[4,113],"widely":[5],"studied":[6],"for":[7,21,48],"low-level":[8],"computer":[9],"vision":[10],"tasks":[11],"and":[12,59,79,96,148],"the":[13,65,133],"Robust":[14],"Principal":[15],"Component":[16],"Analysis":[17],"(RPCA)":[18],"is":[19],"unfolded":[20],"high-level":[22],"task":[23],"of":[24,70,145],"anomaly":[25],"detection,":[26],"almost":[27],"no":[28],"work":[29],"focus":[30],"on":[31],"interpretable":[32],"multi-class":[33,111,126],"semantic":[34],"segmentation":[35,51,55,141],"network.":[36],"To":[37],"resolve":[38],"this":[39],"issue,":[40],"we":[41,88],"propose":[42],"an":[43,104],"edge-aware":[44],"RPCA":[45,106],"optimization":[46,66],"model":[47],"brain":[49],"tissue":[50],"by":[52,116],"formulating":[53],"each-class":[54],"as":[56,93],"non-edge":[57],"estimation":[58],"edge":[60],"prediction.":[61,127],"Firstly,":[62],"according":[63],"to":[64,102],"model,":[67],"three":[68,91,121],"parts":[69,92],"Multi-class":[71,75,80],"Low-rank":[72],"Non-edge-estimation":[73],"(MLN),":[74],"Edge":[76],"Prediction":[77,82],"(MEP)":[78],"Semantic":[81],"(MSP)":[83],"can":[84,136],"be":[85],"formed.":[86],"Secondly,":[87],"unfold":[89],"these":[90,120],"MLN,":[94],"MEP":[95],"MSP":[97],"at":[99],"each":[100,117],"stage":[101],"build":[103],"Edge-aware":[105],"Segmentation":[107],"Network":[108],"(ER-SegNet).":[109],"Thirdly,":[110],"features":[112],"jointly":[114],"leveraged":[115],"one":[118],"among":[119],"rather":[123],"than":[124],"independent":[125],"Experimental":[128],"results":[129],"have":[130],"shown":[131],"that":[132],"proposed":[134],"ER-SegNet":[135],"compete":[137],"against":[138],"many":[139],"newest":[140],"methods":[142],"in":[143],"terms":[144],"pixel":[146],"accuracy":[147],"Dice":[149],"score.":[150]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-30T00:00:00"}