{"id":"https://openalex.org/W2963336955","doi":"https://doi.org/10.1109/tip.2019.2928134","title":"RESLS: Region and Edge Synergetic Level Set Framework for Image Segmentation","display_name":"RESLS: Region and Edge Synergetic Level Set Framework for Image Segmentation","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2963336955","doi":"https://doi.org/10.1109/tip.2019.2928134","mag":"2963336955","pmid":"https://pubmed.ncbi.nlm.nih.gov/31331891"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2019.2928134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2928134","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100743160","display_name":"Weihang Zhang","orcid":"https://orcid.org/0000-0002-6633-1801"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihang Zhang","raw_affiliation_strings":["State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6633-1801","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035550613","display_name":"Xue Wang","orcid":"https://orcid.org/0000-0003-4842-3160"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xue Wang","raw_affiliation_strings":["State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4842-3160","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101576726","display_name":"Wei You","orcid":"https://orcid.org/0000-0001-9729-9763"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei You","raw_affiliation_strings":["State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100426698","display_name":"Junfeng Chen","orcid":"https://orcid.org/0000-0002-2332-7087"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junfeng Chen","raw_affiliation_strings":["State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101406873","display_name":"Peng Dai","orcid":"https://orcid.org/0000-0002-4749-4787"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Dai","raw_affiliation_strings":["State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4749-4787","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100606074","display_name":"Pengbo Zhang","orcid":"https://orcid.org/0000-0002-9296-7053"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengbo Zhang","raw_affiliation_strings":["State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9296-7053","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":3.8709,"has_fulltext":false,"cited_by_count":80,"citation_normalized_percentile":{"value":0.94934486,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"29","issue":null,"first_page":"57","last_page":"71"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9975000023841858,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.995199978351593,"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/image-segmentation","display_name":"Image segmentation","score":0.6496196389198303},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.624137818813324},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6229105591773987},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5837874412536621},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5557587742805481},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5176222920417786},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4680247902870178},{"id":"https://openalex.org/keywords/level-set","display_name":"Level set (data structures)","score":0.45460811257362366},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44681835174560547},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41159629821777344},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3497088551521301}],"concepts":[{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6496196389198303},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.624137818813324},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6229105591773987},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5837874412536621},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5557587742805481},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5176222920417786},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4680247902870178},{"id":"https://openalex.org/C153008295","wikidata":"https://www.wikidata.org/wiki/Q6535093","display_name":"Level set (data structures)","level":2,"score":0.45460811257362366},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44681835174560547},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41159629821777344},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3497088551521301},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2019.2928134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2928134","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:31331891","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31331891","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.7900000214576721,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G1238910806","display_name":null,"funder_award_id":"2018YFB2003500","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5785981196","display_name":null,"funder_award_id":"61472216","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8756530871","display_name":null,"funder_award_id":"2018YFB2003200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"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":52,"referenced_works":["https://openalex.org/W1424614812","https://openalex.org/W1496099826","https://openalex.org/W1903029394","https://openalex.org/W1979393293","https://openalex.org/W1986640343","https://openalex.org/W2006012053","https://openalex.org/W2006673626","https://openalex.org/W2080668963","https://openalex.org/W2104095591","https://openalex.org/W2112891016","https://openalex.org/W2115664739","https://openalex.org/W2116040950","https://openalex.org/W2122184585","https://openalex.org/W2132116135","https://openalex.org/W2144133758","https://openalex.org/W2145803225","https://openalex.org/W2149184914","https://openalex.org/W2159152281","https://openalex.org/W2162837059","https://openalex.org/W2271432203","https://openalex.org/W2296478878","https://openalex.org/W2333052987","https://openalex.org/W2344048381","https://openalex.org/W2412782625","https://openalex.org/W2467514263","https://openalex.org/W2527062305","https://openalex.org/W2586834759","https://openalex.org/W2589644515","https://openalex.org/W2591964073","https://openalex.org/W2595202532","https://openalex.org/W2603234305","https://openalex.org/W2605570189","https://openalex.org/W2626370347","https://openalex.org/W2740997541","https://openalex.org/W2741033153","https://openalex.org/W2742400085","https://openalex.org/W2762439315","https://openalex.org/W2766054123","https://openalex.org/W2770286416","https://openalex.org/W2771234496","https://openalex.org/W2783179424","https://openalex.org/W2785540072","https://openalex.org/W2792945361","https://openalex.org/W2793404847","https://openalex.org/W2800561367","https://openalex.org/W2808829191","https://openalex.org/W2963739249","https://openalex.org/W3100256308","https://openalex.org/W3121626821","https://openalex.org/W4249536100","https://openalex.org/W6677607857","https://openalex.org/W6697590335"],"related_works":["https://openalex.org/W1522196789","https://openalex.org/W2102683994","https://openalex.org/W2063813108","https://openalex.org/W2373659438","https://openalex.org/W2162755489","https://openalex.org/W2006136340","https://openalex.org/W1879755808","https://openalex.org/W2164781768","https://openalex.org/W2097403386","https://openalex.org/W2085099126"],"abstract_inverted_index":{"The":[0,190],"active":[1],"contour":[2],"models":[3,76,131,178],"with":[4,11,225],"level":[5,116,129],"set":[6,117,130],"evolution":[7],"have":[8],"been":[9,33],"visited":[10],"a":[12,111,133],"vast":[13],"number":[14],"of":[15,54,60,89,102,155,187,197,204,219],"methods":[16],"for":[17,95],"image":[18],"segmentation.":[19],"They":[20],"can":[21,45,160,207,221],"be":[22,161,208,222],"mainly":[23],"classified":[24],"into":[25,145],"region-based":[26],"and":[27,30,42,66,98,113,157,216],"edge-based":[28,147],"models,":[29],"it":[31],"has":[32],"validated":[34],"that":[35,138,193],"the":[36,47,52,57,64,67,81,140,146,152,164,170,185,195,198,201,212],"hybrid":[37,75,128],"variants":[38],"combining":[39,79],"both":[40],"region":[41,65,112,141,156],"edge":[43,68,114,158],"information":[44,69,142],"improve":[46],"segmentation":[48,213],"performance.":[49],"However,":[50],"to":[51,125,183],"best":[53],"our":[55,188],"knowledge,":[56],"theoretical":[58],"foundation":[59],"collaboration":[61],"mechanism":[62],"between":[63],"is":[70],"limited.":[71],"Specifically,":[72],"most":[73],"existing":[74],"are":[77,179],"just":[78],"all":[80],"energy":[82,153],"terms":[83,159],"together,":[84],"resulting":[85],"in":[86],"great":[87],"challenges":[88],"choosing":[90],"an":[91,123],"appropriate":[92],"weight":[93],"coefficient":[94],"each":[96,205],"term":[97,206],"accommodating":[99],"different":[100],"modalities":[101],"imaging.":[103],"To":[104],"overcome":[105],"these":[106],"difficulties,":[107],"this":[108,150],"paper":[109],"proposes":[110],"synergetic":[115],"framework":[118],"named":[119],"RESLS.":[120],"It":[121],"provides":[122],"approach":[124],"construct":[126],"new":[127],"using":[132],"normalized":[134],"intensity":[135],"indicator":[136],"function":[137],"allows":[139],"easily":[143],"embedding":[144],"model.":[148],"In":[149],"case,":[151],"weights":[154],"constrained":[162],"by":[163],"global":[165],"optimization":[166,199],"condition":[167],"deduced":[168],"from":[169],"framework.":[171],"Some":[172],"representative":[173],"as":[174,176,181],"well":[175],"state-of-the-art":[177],"taken":[180],"examples":[182],"demonstrate":[184],"generality":[186],"method.":[189],"experiments":[191],"validate":[192],"under":[194],"guidance":[196],"condition,":[200],"weighting":[202],"parameter":[203],"reliably":[209],"chosen.":[210],"Meanwhile,":[211],"accuracy,":[214],"robustness,":[215],"computational":[217],"efficiency":[218],"RESLS":[220],"improved":[223],"compared":[224],"its":[226],"component":[227],"models.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}