{"id":"https://openalex.org/W2913768941","doi":"https://doi.org/10.1109/isbi.2019.8759518","title":"Soft Labeling by Distilling Anatomical Knowledge for Improved MS Lesion Segmentation","display_name":"Soft Labeling by Distilling Anatomical Knowledge for Improved MS Lesion Segmentation","publication_year":2019,"publication_date":"2019-04-01","ids":{"openalex":"https://openalex.org/W2913768941","doi":"https://doi.org/10.1109/isbi.2019.8759518","mag":"2913768941"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2019.8759518","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2019.8759518","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)","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/A5011329007","display_name":"Eytan Kats","orcid":null},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Eytan Kats","raw_affiliation_strings":["Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel","institution_ids":["https://openalex.org/I16391192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005409420","display_name":"Jacob Goldberger","orcid":"https://orcid.org/0000-0002-2225-1914"},"institutions":[{"id":"https://openalex.org/I13955877","display_name":"Bar-Ilan University","ror":"https://ror.org/03kgsv495","country_code":"IL","type":"education","lineage":["https://openalex.org/I13955877"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Jacob Goldberger","raw_affiliation_strings":["Faculty of Engineering, Bar-Ilan University, Ramat-Gan, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Bar-Ilan University, Ramat-Gan, Israel","institution_ids":["https://openalex.org/I13955877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078473649","display_name":"Hayit Greenspan","orcid":"https://orcid.org/0000-0001-6908-7552"},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Hayit Greenspan","raw_affiliation_strings":["Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel","institution_ids":["https://openalex.org/I16391192"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1563","last_page":"1566"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9998000264167786,"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":0.9998000264167786,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9969000220298767,"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/T10862","display_name":"AI in cancer detection","score":0.9897000193595886,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7942509651184082},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7622383236885071},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7278760671615601},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6606557369232178},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6485965847969055},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.6420233249664307},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5223715901374817},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4503907859325409},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44068291783332825},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4196258783340454}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7942509651184082},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7622383236885071},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7278760671615601},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6606557369232178},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6485965847969055},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.6420233249664307},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5223715901374817},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4503907859325409},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44068291783332825},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4196258783340454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2019.8759518","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2019.8759518","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)","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":17,"referenced_works":["https://openalex.org/W1665214252","https://openalex.org/W1821462560","https://openalex.org/W1884191083","https://openalex.org/W1901129140","https://openalex.org/W2291395045","https://openalex.org/W2301358467","https://openalex.org/W2342591535","https://openalex.org/W2575552683","https://openalex.org/W2589409328","https://openalex.org/W2734349601","https://openalex.org/W2787687030","https://openalex.org/W2964098128","https://openalex.org/W6637242042","https://openalex.org/W6638523607","https://openalex.org/W6639824700","https://openalex.org/W6696696767","https://openalex.org/W6748254562"],"related_works":["https://openalex.org/W3027020613","https://openalex.org/W2016533837","https://openalex.org/W3167885074","https://openalex.org/W2892386716","https://openalex.org/W4306164210","https://openalex.org/W4313316311","https://openalex.org/W4362608745","https://openalex.org/W1998563493","https://openalex.org/W2383143032","https://openalex.org/W1522196789"],"abstract_inverted_index":{"This":[0],"paper":[1],"explores":[2],"the":[3,40,58,62,77,81,102,120,129,132,137,141,177],"use":[4],"of":[5,22,30,48,80,101,119],"a":[6,14,34,89,108,125,151,158,184],"soft":[7,94,126,138,171],"ground-truth":[8],"mask":[9,95,105,172],"(\u201csoft":[10],"mask\u201d)":[11],"to":[12,39,75,149,156,183],"train":[13],"Fully":[15],"Convolutional":[16],"Neural":[17],"Network":[18],"(FCNN)":[19],"for":[20,55],"segmentation":[21,29,104,179],"Multiple":[23],"Sclerosis":[24],"(MS)":[25],"lesions.":[26],"Detection":[27],"and":[28,117,155],"MS":[31],"lesions":[32],"is":[33,96,134,147],"complex":[35],"task":[36],"largely":[37],"due":[38],"extreme":[41],"unbalanced":[42],"data,":[43],"with":[44,84],"very":[45],"small":[46],"number":[47],"lesion":[49,63,70,82],"pixels":[50,65],"that":[51,61,167],"can":[52,175],"be":[53],"used":[54],"training.":[56],"Utilizing":[57],"anatomical":[59],"knowledge":[60],"surrounding":[64],"may":[66],"also":[67,165],"include":[68],"some":[69],"level":[71],"information,":[72],"we":[73,174],"suggest":[74],"increase":[76],"data":[78,87],"set":[79],"class":[83],"neighboring":[85],"pixel":[86],"-with":[88],"reduced":[90],"confidence":[91],"weight.":[92],"A":[93],"constructed":[97],"by":[98,107,168],"morphological":[99],"dilation":[100],"binary":[103],"provided":[106],"given":[109],"expert,":[110],"where":[111],"expert-marked":[112],"voxels":[113,118],"receive":[114],"label":[115],"1":[116],"dilated":[121],"region":[122],"are":[123],"assigned":[124],"label.":[127],"In":[128],"methodology":[130],"proposed,":[131],"FCNN":[133],"trained":[135],"using":[136,169],"mask.":[139],"On":[140],"ISBI":[142],"2015":[143],"challenge":[144],"dataset,":[145],"this":[146,170],"shown":[148],"provide":[150],"better":[152],"precision-recall":[153],"tradeoff":[154],"achieve":[157],"higher":[159],"average":[160],"Dice":[161],"similarity":[162],"coefficient.":[163],"We":[164],"show":[166],"scheme":[173],"improve":[176],"network":[178],"performance":[180],"when":[181],"compared":[182],"second":[185],"independent":[186],"expert.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}