{"id":"https://openalex.org/W4402915495","doi":"https://doi.org/10.1109/icip51287.2024.10647711","title":"Quadruple-Consistency Vision Transformer for Medical Image Segmentation with Limited Number of Sparse Annotations","display_name":"Quadruple-Consistency Vision Transformer for Medical Image Segmentation with Limited Number of Sparse Annotations","publication_year":2024,"publication_date":"2024-09-27","ids":{"openalex":"https://openalex.org/W4402915495","doi":"https://doi.org/10.1109/icip51287.2024.10647711"},"language":"en","primary_location":{"id":"doi:10.1109/icip51287.2024.10647711","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icip51287.2024.10647711","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Image Processing (ICIP)","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/A5068621276","display_name":"Yufan Liu","orcid":"https://orcid.org/0000-0002-8426-9335"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yufan Liu","raw_affiliation_strings":["University of California,Department of EECS,Berkeley,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Department of EECS,Berkeley,USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100348425","display_name":"Ziyang Wang","orcid":"https://orcid.org/0009-0006-4832-3345"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ziyang Wang","raw_affiliation_strings":["University of Oxford,Department of Computer Science,UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oxford,Department of Computer Science,UK","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101579762","display_name":"Tianxiang Chen","orcid":"https://orcid.org/0000-0001-5199-7507"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianxiang Chen","raw_affiliation_strings":["University of Science and Technology of China,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China,China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100341722","display_name":"Zi Ye","orcid":"https://orcid.org/0000-0003-1002-0315"},"institutions":[{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zi Ye","raw_affiliation_strings":["Institute of Intelligent Software,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Software,China","institution_ids":["https://openalex.org/I4210128818"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"31","issue":null,"first_page":"2101","last_page":"2107"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9674000144004822,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9674000144004822,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9652000069618225,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9431999921798706,"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/image-segmentation","display_name":"Image segmentation","score":0.6819820404052734},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6757382750511169},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6496877670288086},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6219170093536377},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.571709394454956},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.513599157333374},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4716704785823822},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.4186418950557709},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33277398347854614}],"concepts":[{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6819820404052734},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6757382750511169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6496877670288086},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6219170093536377},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.571709394454956},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.513599157333374},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4716704785823822},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.4186418950557709},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33277398347854614}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip51287.2024.10647711","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icip51287.2024.10647711","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2048679005","https://openalex.org/W2337429362","https://openalex.org/W2412782625","https://openalex.org/W2464708700","https://openalex.org/W2750925197","https://openalex.org/W2751665805","https://openalex.org/W2804047627","https://openalex.org/W2808139377","https://openalex.org/W2884436604","https://openalex.org/W2914363005","https://openalex.org/W2928133111","https://openalex.org/W2951970475","https://openalex.org/W2962804657","https://openalex.org/W2963073217","https://openalex.org/W2979907638","https://openalex.org/W3035680157","https://openalex.org/W3129501203","https://openalex.org/W3138516171","https://openalex.org/W3171581326","https://openalex.org/W3209458476","https://openalex.org/W4295747380","https://openalex.org/W4295934187","https://openalex.org/W4320036903","https://openalex.org/W4321232185","https://openalex.org/W4386598503","https://openalex.org/W4387211241","https://openalex.org/W4387422462","https://openalex.org/W6733814495","https://openalex.org/W6750469568","https://openalex.org/W6751647823","https://openalex.org/W6772553744","https://openalex.org/W6776411772","https://openalex.org/W6790275670","https://openalex.org/W6810755270","https://openalex.org/W6841980587"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2945274617","https://openalex.org/W1986655823","https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W2055202857","https://openalex.org/W2371519352","https://openalex.org/W4205800335","https://openalex.org/W2386644571","https://openalex.org/W2372421320"],"abstract_inverted_index":{"Deep":[0],"learning":[1,56],"has":[2],"significantly":[3],"advanced":[4,105],"the":[5,30,80,88,100,115,121,161],"field":[6],"of":[7,51,66,73,91,128],"medical":[8],"image":[9,97],"segmentation":[10,140],"but":[11],"typically":[12],"relies":[13],"on":[14,87,134],"extensive,":[15],"densely":[16],"annotated":[17],"datasets,":[18],"which":[19,47,85],"are":[20],"both":[21,62,114],"costly":[22],"and":[23,54,69,117,124,160],"time-consuming":[24],"to":[25,29],"prepare.":[26],"In":[27],"response":[28],"need":[31],"for":[32],"reducing":[33],"annotation":[34],"efforts,":[35],"this":[36],"study":[37],"investigates":[38],"a":[39,49,63,70,135],"novel":[40],"supervision":[41],"approach":[42,60],"named":[43],"Semi-Scribble":[44],"Supervised":[45],"Learning,":[46],"utilizes":[48],"combination":[50],"semi-supervised":[52],"(SSL)":[53],"weaklysupervised":[55],"(WSL)":[57],"techniques.":[58],"This":[59],"leverages":[61],"large":[64],"volume":[65],"unlabeled":[67],"data":[68,116],"smaller":[71],"set":[72],"sparsely":[74],"annotated,":[75],"scribble-based":[76],"labels.":[77],"We":[78],"introduce":[79],"Quadruple-Consistency":[81],"Vision":[82,92],"Transformer":[83],"(4C-ViT),":[84],"capitalizes":[86],"recent":[89],"success":[90],"Transformers":[93],"in":[94],"capturing":[95],"intricate":[96],"features.":[98],"Specifically,":[99],"proposed":[101,153],"4C-ViT":[102],"employs":[103],"an":[104],"consistency":[106],"training":[107],"strategy":[108],"that":[109],"incorporates":[110],"quadruple":[111],"perturbations":[112],"at":[113,170],"network":[118],"levels,":[119],"enhancing":[120],"network\u2019s":[122],"robustness":[123],"performance.":[125],"The":[126,152],"efficacy":[127],"4":[129],"C":[130],"-ViT":[131],"is":[132,166],"demonstrated":[133],"publicly":[136],"available":[137,169],"MRI":[138],"cardiac":[139],"benchmark,":[141],"where":[142],"it":[143],"outperforms":[144],"other":[145],"baseline":[146,158],"methods":[147,159],"across":[148],"several":[149],"evaluation":[150],"metrics.":[151],"$4":[154],"\\mathrm{C}-\\mathrm{ViT}$,":[155],"alongside":[156],"all":[157],"challenging":[162],"yet":[163],"realistic":[164],"dataset,":[165],"made":[167],"public":[168],"https://github.com/ziyangwang007/CVSSL-MIS.":[171]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}