{"id":"https://openalex.org/W4406612377","doi":"https://doi.org/10.1109/smc54092.2024.10831461","title":"SIDN-NAS: Scalable Iterative Dense Network with Neural Architecture Search Optimization for Medical Image Segmentation","display_name":"SIDN-NAS: Scalable Iterative Dense Network with Neural Architecture Search Optimization for Medical Image Segmentation","publication_year":2024,"publication_date":"2024-10-06","ids":{"openalex":"https://openalex.org/W4406612377","doi":"https://doi.org/10.1109/smc54092.2024.10831461"},"language":"en","primary_location":{"id":"doi:10.1109/smc54092.2024.10831461","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc54092.2024.10831461","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 Systems, Man, and Cybernetics (SMC)","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/A5021641420","display_name":"Jianjun Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianjun Zhou","raw_affiliation_strings":["School of Software Engineering, South China University of Technology,Guangzhou,China,510006"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, South China University of Technology,Guangzhou,China,510006","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101953157","display_name":"Junying Chen","orcid":"https://orcid.org/0000-0003-3881-7238"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junying Chen","raw_affiliation_strings":["School of Software Engineering, South China University of Technology,Guangzhou,China,510006"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, South China University of Technology,Guangzhou,China,510006","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5021641420"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":0.3637,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.7094649,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"2297","last_page":"2304"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9757000207901001,"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/T10862","display_name":"AI in cancer detection","score":0.9757000207901001,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9750000238418579,"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":0.9725000262260437,"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/computer-science","display_name":"Computer science","score":0.77297043800354},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6486304402351379},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5856057405471802},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5349852442741394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5313271880149841},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5180649757385254},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5076550245285034},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.45451873540878296},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4152463972568512},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39410507678985596},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.0600319504737854}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.77297043800354},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6486304402351379},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5856057405471802},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5349852442741394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5313271880149841},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5180649757385254},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5076550245285034},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.45451873540878296},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4152463972568512},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39410507678985596},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0600319504737854},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc54092.2024.10831461","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc54092.2024.10831461","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 Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4000000059604645,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2547875792","https://openalex.org/W2592905743","https://openalex.org/W2735039185","https://openalex.org/W2885343725","https://openalex.org/W2921406441","https://openalex.org/W2927980542","https://openalex.org/W2963136578","https://openalex.org/W2980294132","https://openalex.org/W3002569343","https://openalex.org/W3013198566","https://openalex.org/W3088257970","https://openalex.org/W3092618738","https://openalex.org/W3132503749","https://openalex.org/W3204725823","https://openalex.org/W4289752563","https://openalex.org/W4312203639","https://openalex.org/W4382998948","https://openalex.org/W6748775820","https://openalex.org/W6750469568","https://openalex.org/W6752515464","https://openalex.org/W6790275670"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W2965083567","https://openalex.org/W4235240664","https://openalex.org/W1838576100","https://openalex.org/W2095886385","https://openalex.org/W2889616422","https://openalex.org/W2089704382","https://openalex.org/W1983399550","https://openalex.org/W97075385","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Medical":[0],"image":[1,36,44,66,83,180],"segmentation":[2,37,45,67,84,152,168],"faces":[3],"problems":[4],"such":[5],"as":[6],"the":[7,16,28,41,47,52,56,59,63,130,146,151,167,184,197,211],"unbalanced":[8],"foreground":[9],"and":[10,15,32,58,114,123,149,158,166,196],"background":[11],"of":[12,62,99,186,199],"medical":[13,35,43,65,82,179],"images":[14],"limited":[17],"dataset":[18],"size.":[19],"Meanwhile,":[20],"Neural":[21],"Architecture":[22],"Search":[23],"(NAS)":[24],"methods":[25,49],"have":[26],"shown":[27],"great":[29],"application":[30],"potential":[31],"value":[33],"in":[34,109],"tasks.":[38],"Compared":[39],"to":[40,143,175,194,206],"manually-designed":[42],"models,":[46],"NAS":[48,92,141,159],"can":[50,126],"improve":[51,150],"model":[53,68,85,97,147,156,187,212],"accuracy,":[54],"but":[55,79],"complexity":[57,148],"computing":[60],"cost":[61],"searched":[64],"is":[69,218],"relatively":[70],"high.":[71],"In":[72],"this":[73],"work,":[74],"we":[75],"propose":[76],"a":[77,139],"high-precision":[78],"low-complexity":[80],"scalable":[81,100],"(Scalable":[86],"Iterative":[87],"Dense":[88],"Network,":[89],"SIDN)":[90],"with":[91],"optimization.":[93],"The":[94,154],"proposed":[95],"SIDN":[96,155],"consists":[98],"iterative":[101],"U-shape":[102],"encoder/decoder":[103],"stacks,":[104],"uses":[105,138],"fewer":[106],"convolutional":[107],"kernels":[108],"each":[110],"encoder":[111],"or":[112],"decoder":[113],"performs":[115],"dense":[116],"multi-scale":[117],"residual":[118],"semantic":[119,131],"connections":[120],"between":[121,133],"encoders":[122],"decoders,":[124],"which":[125],"make":[127],"up":[128],"for":[129],"differences":[132],"different":[134],"levels.":[135],"It":[136],"then":[137],"gradient-based":[140],"algorithm":[142],"further":[144],"reduce":[145],"accuracy.":[153],"training":[157],"optimization":[160],"only":[161],"require":[162],"1":[163],"GPU":[164],"hour,":[165],"accuracy":[169],"has":[170,189,201],"been":[171,190,202],"improved":[172],"by":[173,192,204],"7%":[174],"10%":[176],"on":[177],"multiple":[178],"datasets.":[181],"More":[182],"importantly,":[183],"number":[185],"parameters":[188],"reduced":[191,203],"31%":[193],"88%,":[195],"amount":[198],"calculation":[200],"32%":[205],"44":[207],"%,":[208],"greatly":[209],"improving":[210],"inference":[213],"speed.":[214],"Our":[215],"source":[216],"code":[217],"available":[219],"at:":[220],"https://github.com/Bob5090/SIDN-NAS.":[221]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
