{"id":"https://openalex.org/W4200346246","doi":"https://doi.org/10.1109/iscmi53840.2021.9654807","title":"Unsupervised Learning Reduces Local Image Redundancy and Improves Supervised Segmentation of Dermoscopy Lesions","display_name":"Unsupervised Learning Reduces Local Image Redundancy and Improves Supervised Segmentation of Dermoscopy Lesions","publication_year":2021,"publication_date":"2021-11-26","ids":{"openalex":"https://openalex.org/W4200346246","doi":"https://doi.org/10.1109/iscmi53840.2021.9654807"},"language":"en","primary_location":{"id":"doi:10.1109/iscmi53840.2021.9654807","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscmi53840.2021.9654807","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 8th International Conference on Soft Computing & Machine Intelligence (ISCMI)","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/A5008126724","display_name":"Qiaoer Zhou","orcid":"https://orcid.org/0000-0001-8439-7305"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiaoer Zhou","raw_affiliation_strings":["College of Biomedical Engineering Sichuan University,Chengdu,People‘s Republic of China"],"affiliations":[{"raw_affiliation_string":"College of Biomedical Engineering Sichuan University,Chengdu,People‘s Republic of China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086602447","display_name":"Parsa Akbari","orcid":"https://orcid.org/0000-0001-9210-4760"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Parsa Akbari","raw_affiliation_strings":["Downing College,Cambridge,United Kingdom,CB2 1DQ"],"affiliations":[{"raw_affiliation_string":"Downing College,Cambridge,United Kingdom,CB2 1DQ","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004370357","display_name":"Yuanwen Zou","orcid":"https://orcid.org/0000-0002-9228-3698"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanwen Zou","raw_affiliation_strings":["College of Biomedical Engineering Sichuan University,Chengdu,People‘s Republic of China"],"affiliations":[{"raw_affiliation_string":"College of Biomedical Engineering Sichuan University,Chengdu,People‘s Republic of China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008126724"],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":0.089,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49352251,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"247","last_page":"252"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T11013","display_name":"Skin Protection and Aging","score":0.9865000247955322,"subfield":{"id":"https://openalex.org/subfields/2708","display_name":"Dermatology"},"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/T11306","display_name":"Nonmelanoma Skin Cancer Studies","score":0.9790999889373779,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7914989590644836},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7118596434593201},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6822444200515747},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6667928695678711},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6181118488311768},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5452739000320435},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.5392012000083923},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.537348210811615},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5157768726348877},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.451660692691803},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4277610778808594}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7914989590644836},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7118596434593201},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6822444200515747},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6667928695678711},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6181118488311768},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5452739000320435},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.5392012000083923},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.537348210811615},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5157768726348877},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.451660692691803},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4277610778808594},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscmi53840.2021.9654807","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscmi53840.2021.9654807","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 8th International Conference on Soft Computing & Machine Intelligence (ISCMI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1901129140","https://openalex.org/W1923697677","https://openalex.org/W1986985050","https://openalex.org/W1992102496","https://openalex.org/W1992230791","https://openalex.org/W2033870996","https://openalex.org/W2049748121","https://openalex.org/W2104125540","https://openalex.org/W2112973039","https://openalex.org/W2116930734","https://openalex.org/W2118246710","https://openalex.org/W2121947440","https://openalex.org/W2129872026","https://openalex.org/W2142259554","https://openalex.org/W2161236525","https://openalex.org/W2607363228","https://openalex.org/W2753863096","https://openalex.org/W2809209815","https://openalex.org/W2932083555","https://openalex.org/W2952793010","https://openalex.org/W2962767316","https://openalex.org/W2980039210","https://openalex.org/W2987039128","https://openalex.org/W2996717109","https://openalex.org/W3037210452","https://openalex.org/W3102785203","https://openalex.org/W4295815778","https://openalex.org/W6631190155","https://openalex.org/W6640295612","https://openalex.org/W6662855644","https://openalex.org/W6677945368","https://openalex.org/W6760107785"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2185902295","https://openalex.org/W2945274617","https://openalex.org/W2372421320","https://openalex.org/W2057775483","https://openalex.org/W2041871225","https://openalex.org/W2386644571","https://openalex.org/W4205800335","https://openalex.org/W2387793296","https://openalex.org/W1558398159"],"abstract_inverted_index":{"Melanoma":[0],"is":[1,36,156],"the":[2,37,51,99,111,125,130,143,186,189,197],"most":[3],"common":[4],"form":[5],"of":[6,21,27,40,53,114,124,188,199],"skin":[7,10,22,84,115],"cancer,":[8],"and":[9,30,72,98,134,180],"disease":[11,85],"image":[12,28,70,86,133,136,159,201],"segmentation":[13,29,56,78,87,122],"plays":[14],"a":[15,83,150],"vital":[16],"role":[17],"in":[18,74,77,183],"automated":[19,32],"diagnosis":[20],"cancer.":[23],"A":[24],"primary":[25],"challenge":[26],"other":[31],"object":[33],"recognition":[34],"techniques":[35],"large":[38],"amount":[39],"redundant":[41],"input":[42,48,65,140],"information":[43,141],"which":[44],"often":[45],"obfuscates":[46],"critical":[47,118],"features.":[49],"In":[50],"context":[52],"dermatoscopy":[54],"lesion":[55],"we":[57],"show":[58],"that":[59,120,193],"unsupervised":[60,91,106],"clustering":[61],"algorithms":[62],"applied":[63],"to":[64],"images":[66],"can":[67,109],"reduce":[68],"local":[69],"redundancy":[71],"result":[73],"dramatic":[75],"improvements":[76],"performance.":[79],"Our":[80],"work":[81],"proposes":[82],"algorithm":[88,96,162],"combining":[89],"an":[90,164],"simple":[92],"linear":[93],"iterative":[94],"cluster":[95],"(SLIC),":[97],"supervised":[100,126],"deep":[101,146],"learning":[102,147],"U-Net":[103,127,144],"model.":[104,128,148],"The":[105],"SLIC":[107],"method":[108],"detect":[110],"fine":[112],"structure":[113],"damage":[116],"highlighting":[117],"features":[119],"improve":[121],"performance":[123,198],"Both":[129],"superpixel":[131],"dermoscope":[132],"original":[135],"are":[137],"used":[138,157],"as":[139],"for":[142,158],"training":[145],"Finally,":[149],"fully-connected":[151],"conditional":[152],"random":[153],"field":[154],"(CRF)":[155],"post-processing.":[160],"This":[161],"achieves":[163],"Intersection":[165],"Over":[166],"Unit(IOU)":[167],"coefficient":[168,172],"reaching":[169],"83%,":[170],"dice":[171],"90%,":[173,175],"sensitivity":[174],"improved":[176],"by":[177],"10%,":[178],"7%":[179],"4%":[181],"respectively":[182],"comparison":[184],"with":[185],"results":[187],"classic":[190],"U-Net,":[191],"showing":[192],"this":[194],"approach":[195],"improves":[196],"network":[200],"segmentation.":[202]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}