{"id":"https://openalex.org/W2884239853","doi":"https://doi.org/10.1109/icdsp.2018.8631858","title":"A post-processing method to improve the white matter hyperintensity segmentation accuracy for randomly-initialized U-net","display_name":"A post-processing method to improve the white matter hyperintensity segmentation accuracy for randomly-initialized U-net","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2884239853","doi":"https://doi.org/10.1109/icdsp.2018.8631858","mag":"2884239853"},"language":"en","primary_location":{"id":"doi:10.1109/icdsp.2018.8631858","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2018.8631858","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","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/A5100333699","display_name":"Yue Zhang","orcid":"https://orcid.org/0009-0002-8996-8159"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Zhang","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078997270","display_name":"Wanli Chen","orcid":"https://orcid.org/0000-0002-4507-2177"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanli Chen","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100405124","display_name":"Yifan Chen","orcid":"https://orcid.org/0000-0001-7645-623X"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Chen","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001406512","display_name":"Xiaoying Tang","orcid":"https://orcid.org/0000-0002-9610-0318"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoying Tang","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.555,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.69497584,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9990000128746033,"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":0.9983999729156494,"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/initialization","display_name":"Initialization","score":0.8170042634010315},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.7846968173980713},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7820205688476562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7384759187698364},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6693267822265625},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.643290102481842},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6010125875473022},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.487638384103775},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3682284355163574}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.8170042634010315},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.7846968173980713},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7820205688476562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7384759187698364},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6693267822265625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.643290102481842},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6010125875473022},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.487638384103775},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3682284355163574},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdsp.2018.8631858","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2018.8631858","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327250","display_name":"National University Health System","ror":"https://ror.org/05tjjsh18"},{"id":"https://openalex.org/F4320329174","display_name":"Shenzhen Municipal Science and Technology Innovation Council","ror":"https://ror.org/017n8df75"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W104184427","https://openalex.org/W217970951","https://openalex.org/W1533861849","https://openalex.org/W2138857742","https://openalex.org/W2144971762","https://openalex.org/W2521068627","https://openalex.org/W2532750509","https://openalex.org/W2589409328","https://openalex.org/W2592929672","https://openalex.org/W2787769342","https://openalex.org/W2790867086"],"related_works":["https://openalex.org/W2138983844","https://openalex.org/W1968965685","https://openalex.org/W2012792772","https://openalex.org/W2356573839","https://openalex.org/W2111883783","https://openalex.org/W2009028679","https://openalex.org/W2357424838","https://openalex.org/W2327601824","https://openalex.org/W4237142086","https://openalex.org/W2161102362"],"abstract_inverted_index":{"White":[0],"matter":[1],"hyperintensity":[2],"(WMH)":[3],"is":[4,19,43,161,187,191],"commonly":[5],"found":[6],"in":[7,51],"elder":[8],"individuals":[9],"and":[10,74,105,124,144,189],"appears":[11],"to":[12,38,46,59,119,130,174],"be":[13,172],"associated":[14],"with":[15,63,80],"brain":[16],"diseases.":[17],"U-net":[18,33],"a":[20,70,97],"convolutional":[21],"network":[22],"that":[23],"has":[24,34],"been":[25,35],"widely":[26],"used":[27,45],"for":[28],"biomedical":[29],"image":[30],"segmentation.":[31,40,135],"Recently,":[32],"successfully":[36],"applied":[37,173],"WMH":[39,88,134],"Random":[41],"initialization":[42,186],"usally":[44],"initialize":[47],"the":[48,52,55,76,87,101,113,132,140,151,155,164],"model":[49,56,165],"weights":[50],"U-net.":[53],"However,":[54],"may":[57],"coverage":[58],"different":[60,64,81],"local":[61],"optima":[62],"randomly":[65],"initialized":[66],"weights.":[67],"We":[68],"find":[69],"combination":[71],"of":[72,78,154,163],"thresholding":[73,106,123],"averaging":[75,104],"outputs":[77],"U-nets":[79,118],"random":[82,185],"initializations":[83],"can":[84,170],"largely":[85],"improve":[86],"segmentation":[89],"accuracy.":[90],"Based":[91],"on":[92],"this":[93],"observation,":[94],"we":[95,110],"propose":[96],"post-processing":[98,159],"technique":[99,160],"concerning":[100],"way":[102],"how":[103],"are":[107,181],"conducted.":[108],"Specifically,":[109],"first":[111],"transfer":[112],"score":[114],"maps":[115],"from":[116],"three":[117],"binary":[120,128],"masks":[121,129],"via":[122],"then":[125],"average":[126],"those":[127],"obtain":[131],"final":[133],"Both":[136],"quantitative":[137],"analysis":[138,146],"(via":[139,147],"Dice":[141],"similarity":[142],"coefficient)":[143],"qualitative":[145],"visual":[148],"examinations)":[149],"reveal":[150],"superior":[152],"performance":[153],"proposed":[156],"method.":[157],"This":[158],"independent":[162],"used.":[166],"As":[167],"such,":[168],"it":[169],"also":[171],"situations":[175],"where":[176],"other":[177],"deep":[178],"learning":[179],"models":[180],"employed,":[182],"especially":[183],"when":[184],"adopted":[188],"pre-training":[190],"unavailable.":[192]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
