{"id":"https://openalex.org/W4403791863","doi":"https://doi.org/10.1145/3664647.3681033","title":"BSBP-RWKV: Background Suppression with Boundary Preservation for Efficient Medical Image Segmentation","display_name":"BSBP-RWKV: Background Suppression with Boundary Preservation for Efficient Medical Image Segmentation","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403791863","doi":"https://doi.org/10.1145/3664647.3681033"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3681033","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","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/A5060581855","display_name":"X. R. Zhou","orcid":null},"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"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I2802624667","display_name":"Hefei Institutes of Physical Science","ror":"https://ror.org/046n57345","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I2802624667"]},{"id":"https://openalex.org/I4210099079","display_name":"Institute of Intelligent Machines","ror":"https://ror.org/00w0qep84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I2802624667","https://openalex.org/I4210099079"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xudong Zhou","raw_affiliation_strings":["Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences & University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences & University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I2802624667","https://openalex.org/I4210099079","https://openalex.org/I19820366","https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050671031","display_name":"Tianxiang Chen","orcid":"https://orcid.org/0000-0002-7758-699X"},"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, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5060581855"],"corresponding_institution_ids":["https://openalex.org/I126520041","https://openalex.org/I19820366","https://openalex.org/I2802624667","https://openalex.org/I4210099079"],"apc_list":null,"apc_paid":null,"fwci":3.6399,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.9349023,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"4938","last_page":"4946"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9994000196456909,"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":0.9988999962806702,"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":0.694156289100647},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6688817739486694},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6205715537071228},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6096820831298828},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.5475018620491028},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5270602703094482},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.49104809761047363},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2039467692375183},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.053576529026031494}],"concepts":[{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.694156289100647},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6688817739486694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6205715537071228},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6096820831298828},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5475018620491028},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5270602703094482},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.49104809761047363},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2039467692375183},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.053576529026031494}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3664647.3681033","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2114898750","https://openalex.org/W2150134853","https://openalex.org/W2194775991","https://openalex.org/W2560023338","https://openalex.org/W2579226701","https://openalex.org/W2600297185","https://openalex.org/W2734349601","https://openalex.org/W2964309882","https://openalex.org/W2997286550","https://openalex.org/W3027763298","https://openalex.org/W3092344722","https://openalex.org/W3112701542","https://openalex.org/W4214493665","https://openalex.org/W4287225564","https://openalex.org/W4327661973","https://openalex.org/W4362574915","https://openalex.org/W4362602094","https://openalex.org/W4372184688","https://openalex.org/W4385516366","https://openalex.org/W4385765253","https://openalex.org/W4386400246","https://openalex.org/W4387842347","https://openalex.org/W4393154727","https://openalex.org/W4400238700","https://openalex.org/W6732678756"],"related_works":["https://openalex.org/W1986655823","https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W3011384228","https://openalex.org/W2124969951","https://openalex.org/W2945274617","https://openalex.org/W4313052709","https://openalex.org/W4298131179","https://openalex.org/W2375430703"],"abstract_inverted_index":{"Medical":[0],"image":[1,72,216],"segmentation":[2,30],"is":[3],"of":[4,43,79,104,112,162,187,194],"great":[5],"significance":[6],"to":[7,23,53,108,132,139],"disease":[8],"diagnosis":[9],"and":[10,32,58,64,69,90,96,172,179,185],"treatment":[11],"planning.":[12],"Despite":[13],"multiple":[14],"progresses,":[15],"most":[16],"present":[17],"methods":[18],"(1)":[19],"pay":[20],"insufficient":[21],"attention":[22],"suppressing":[24,116],"background":[25,117],"noise":[26,84,118],"disturbance":[27,119],"that":[28,157],"impacts":[29],"accuracy":[31,184],"(2)":[33],"are":[34,42],"not":[35],"efficient":[36,61,70,94,122],"enough,":[37],"especially":[38],"when":[39],"the":[40,48,77,98,127,141,160,182,199],"images":[41],"large":[44],"resolutions.":[45],"To":[46],"address":[47],"two":[49],"challenges,":[50],"we":[51,75,125],"turn":[52],"a":[54,59,150],"traditional":[55],"de-noising":[56],"method":[57],"new":[60],"network":[62],"structure":[63],"propose":[65,149],"BSBP-RWKV":[66,191],"for":[67,154,211],"accurate":[68],"medical":[71],"segmentation.":[73],"Specifically,":[74,190],"combine":[76],"advantages":[78],"Perona-Malik":[80],"Diffusion":[81],"(PMD)":[82],"in":[83,92,120,169],"suppression":[85],"without":[86],"losing":[87],"boundary":[88,110,130],"details":[89,111],"RWKV":[91,100],"its":[93],"structure,":[95],"devise":[97],"DWT-PMD":[99],"Block":[101,138],"across":[102],"one":[103],"our":[105,133,188],"encoder":[106],"branches":[107],"preserve":[109],"lesion":[113,129,164],"areas":[114,165],"while":[115,201],"an":[121],"structure.":[123],"Then":[124],"feed":[126],"de-noised":[128],"cues":[131,142],"proposed":[134],"Multi-Step":[135],"Runge-Kutta":[136],"convolutional":[137],"supplement":[140],"with":[143,166,198],"more":[144],"local":[145],"details.":[146],"We":[147],"also":[148,202],"novel":[151],"loss":[152],"function":[153],"shape":[155,161],"refinement":[156],"can":[158],"align":[159],"predicted":[163],"GT":[167],"masks":[168],"both":[170],"spatial":[171],"frequency":[173],"domains.":[174],"Experiments":[175],"on":[176],"ISIC":[177],"2016":[178],"Kvasir-SEG":[180],"show":[181],"superior":[183],"efficiency":[186],"BSBP-RWKV.":[189],"reduces":[192],"complexity":[193],"5.8":[195],"times":[196],"compared":[197],"SOTA":[200],"cutting":[203],"down":[204],"GPU":[205],"memory":[206],"usage":[207],"by":[208],"over":[209],"62.7%":[210],"each":[212],"1024":[213,215],"\\times":[214],"during":[217],"inference.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}