{"id":"https://openalex.org/W2806409113","doi":"https://doi.org/10.1109/isbi.2018.8363707","title":"Adversarial learning with multi-scale loss for skin lesion segmentation","display_name":"Adversarial learning with multi-scale loss for skin lesion segmentation","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2806409113","doi":"https://doi.org/10.1109/isbi.2018.8363707","mag":"2806409113"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2018.8363707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363707","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","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/A5028544932","display_name":"Yuan Xue","orcid":"https://orcid.org/0000-0002-5390-9037"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yuan Xue","raw_affiliation_strings":["Lehigh University, Department of Computer Science and Engineering, Bethlehem, PA#TAB#"],"affiliations":[{"raw_affiliation_string":"Lehigh University, Department of Computer Science and Engineering, Bethlehem, PA#TAB#","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100621909","display_name":"Tao Xu","orcid":"https://orcid.org/0000-0003-3705-4152"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tao Xu","raw_affiliation_strings":["Lehigh University, Department of Computer Science and Engineering, Bethlehem, PA#TAB#"],"affiliations":[{"raw_affiliation_string":"Lehigh University, Department of Computer Science and Engineering, Bethlehem, PA#TAB#","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000467703","display_name":"Xiaolei Huang","orcid":"https://orcid.org/0000-0003-2338-6535"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaolei Huang","raw_affiliation_strings":["Lehigh University, Department of Computer Science and Engineering, Bethlehem, PA#TAB#"],"affiliations":[{"raw_affiliation_string":"Lehigh University, Department of Computer Science and Engineering, Bethlehem, PA#TAB#","institution_ids":["https://openalex.org/I186143895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028544932"],"corresponding_institution_ids":["https://openalex.org/I186143895"],"apc_list":null,"apc_paid":null,"fwci":1.9821,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.89538692,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"859","last_page":"863"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9991999864578247,"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":0.9991999864578247,"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/T10862","display_name":"AI in cancer detection","score":0.9879000186920166,"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/T11713","display_name":"Genital Health and Disease","score":0.9230999946594238,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/segmentation","display_name":"Segmentation","score":0.7275168895721436},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7232997417449951},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6684346199035645},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6539770364761353},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.6084250211715698},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.496966153383255},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44072195887565613},{"id":"https://openalex.org/keywords/skin-lesion","display_name":"Skin lesion","score":0.4156641960144043},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39077186584472656},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.334593266248703},{"id":"https://openalex.org/keywords/dermatology","display_name":"Dermatology","score":0.16240531206130981},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.12399044632911682},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.11874926090240479},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06001615524291992}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7275168895721436},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7232997417449951},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6684346199035645},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6539770364761353},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6084250211715698},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.496966153383255},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44072195887565613},{"id":"https://openalex.org/C2988168687","wikidata":"https://www.wikidata.org/wiki/Q949302","display_name":"Skin lesion","level":2,"score":0.4156641960144043},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39077186584472656},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.334593266248703},{"id":"https://openalex.org/C16005928","wikidata":"https://www.wikidata.org/wiki/Q171171","display_name":"Dermatology","level":1,"score":0.16240531206130981},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.12399044632911682},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.11874926090240479},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06001615524291992}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2018.8363707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363707","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1745334888","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1923697677","https://openalex.org/W2554423077","https://openalex.org/W2581082771","https://openalex.org/W2597394795","https://openalex.org/W2598666589","https://openalex.org/W2952147788","https://openalex.org/W2963073614","https://openalex.org/W2963373786","https://openalex.org/W2963563573","https://openalex.org/W2963946669","https://openalex.org/W2964024144","https://openalex.org/W2964201867","https://openalex.org/W3101639073","https://openalex.org/W3105311500","https://openalex.org/W4301462804","https://openalex.org/W4320013936","https://openalex.org/W6639824700","https://openalex.org/W6640295612","https://openalex.org/W6718379498","https://openalex.org/W6730411969"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W4246396837","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W2482350142","https://openalex.org/W1561927205","https://openalex.org/W1522196789","https://openalex.org/W2933370232","https://openalex.org/W2948399186","https://openalex.org/W2883158803"],"abstract_inverted_index":{"Inspired":[0],"by":[1],"classic":[2,38],"Generative":[3],"Adversarial":[4],"Networks":[5],"(GAN),":[6],"we":[7,55],"propose":[8,79],"a":[9,37,57,80,86,119],"novel":[10,81],"end-to-end":[11],"adversarial":[12,82],"neural":[13,60],"network,":[14],"called":[15],"SegAN,":[16],"for":[17],"the":[18,31,52,67,71,95,126,142],"task":[19,128],"of":[20,36],"medical":[21],"image":[22,25],"segmentation.":[23],"Since":[24],"segmentation":[26,75,127,139],"requires":[27],"dense,":[28],"pixel-level":[29],"labeling,":[30],"single":[32],"scalar":[33],"real/fake":[34],"output":[35],"GAN's":[39],"discriminator":[40],"may":[41],"be":[42],"ineffective":[43],"in":[44,66,125,141],"producing":[45],"stable":[46,131],"and":[47,78,97,103,109,129,134],"sufficient":[48],"gradient":[49],"feedback":[50],"to":[51,73,93,99,132],"networks.":[53],"Instead,":[54],"use":[56],"fully":[58],"convolutional":[59],"network":[61,84],"with":[62,85],"new":[63],"activation":[64],"function":[65,92],"last":[68],"layer":[69],"as":[70],"segmentor":[72,98],"generate":[74],"label":[76],"maps,":[77],"critic":[83,96],"multi-scale":[87],"L":[88],"1":[89],"loss":[91],"force":[94],"learn":[100],"both":[101],"global":[102],"local":[104],"features":[105],"that":[106,117],"capture":[107],"long-":[108],"short-range":[110],"spatial":[111],"relationships":[112],"between":[113],"pixels.":[114],"We":[115],"show":[116],"such":[118],"SegAN":[120],"framework":[121],"is":[122],"more":[123,130],"effective":[124],"train,":[133],"it":[135],"outperforms":[136],"current":[137],"state-of-the-art":[138],"methods":[140],"ISBI":[143],"International":[144],"Skin":[145],"Imaging":[146],"Collaboration":[147],"(ISIC)":[148],"2017":[149],"challenge,":[150],"Part":[151],"I":[152],"Lesion":[153],"Segmentation.":[154]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}