{"id":"https://openalex.org/W4293530432","doi":"https://doi.org/10.3390/e24091199","title":"Brain Tumor Segmentation Based on Bendlet Transform and Improved Chan-Vese Model","display_name":"Brain Tumor Segmentation Based on Bendlet Transform and Improved Chan-Vese Model","publication_year":2022,"publication_date":"2022-08-27","ids":{"openalex":"https://openalex.org/W4293530432","doi":"https://doi.org/10.3390/e24091199","pmid":"https://pubmed.ncbi.nlm.nih.gov/36141085"},"language":"en","primary_location":{"id":"doi:10.3390/e24091199","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24091199","pdf_url":"https://www.mdpi.com/1099-4300/24/9/1199/pdf?version=1663734342","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/24/9/1199/pdf?version=1663734342","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090859054","display_name":"Kexin Meng","orcid":"https://orcid.org/0009-0005-9459-3250"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kexin Meng","raw_affiliation_strings":["College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077429359","display_name":"Piercarlo Cattani","orcid":null},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Piercarlo Cattani","raw_affiliation_strings":["Department of Computer, Control and Management Engineering, University of Rome \u201cLa Sapienza\u201d, Via Ariosto 25, 00185 Roma, Italy","Department of Computer, Control and Management Engineering, University of Rome \"La Sapienza\", Via Ariosto 25, 00185 Roma, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer, Control and Management Engineering, University of Rome \u201cLa Sapienza\u201d, Via Ariosto 25, 00185 Roma, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"Department of Computer, Control and Management Engineering, University of Rome \"La Sapienza\", Via Ariosto 25, 00185 Roma, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087487622","display_name":"Francesco Villecco","orcid":"https://orcid.org/0000-0001-6545-4589"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Francesco Villecco","raw_affiliation_strings":["Department of Industrial Engineering, University of Salerno, via Giovanni Paolo II 132, 84084 Fisciano, Italy"],"raw_orcid":"https://orcid.org/0000-0001-6545-4589","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, University of Salerno, via Giovanni Paolo II 132, 84084 Fisciano, Italy","institution_ids":["https://openalex.org/I131729948"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5087487622"],"corresponding_institution_ids":["https://openalex.org/I131729948"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":1.3193,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.81562625,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"24","issue":"9","first_page":"1199","last_page":"1199"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation 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"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation 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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9966999888420105,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.753537654876709},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6167250871658325},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5662129521369934},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5557281374931335},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.5215815901756287},{"id":"https://openalex.org/keywords/level-set","display_name":"Level set (data structures)","score":0.5198472142219543},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5122086405754089},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4923945665359497},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4571703374385834},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4538326561450958},{"id":"https://openalex.org/keywords/level-set-method","display_name":"Level set method","score":0.4345543384552002},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4330741763114929},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.3400065302848816}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.753537654876709},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6167250871658325},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5662129521369934},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5557281374931335},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5215815901756287},{"id":"https://openalex.org/C153008295","wikidata":"https://www.wikidata.org/wiki/Q6535093","display_name":"Level set (data structures)","level":2,"score":0.5198472142219543},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5122086405754089},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4923945665359497},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4571703374385834},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4538326561450958},{"id":"https://openalex.org/C125269122","wikidata":"https://www.wikidata.org/wiki/Q1751397","display_name":"Level set method","level":4,"score":0.4345543384552002},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4330741763114929},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.3400065302848816},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e24091199","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24091199","pdf_url":"https://www.mdpi.com/1099-4300/24/9/1199/pdf?version=1663734342","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:36141085","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36141085","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":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:05f0e5ec5b7e4334958fd9da1e24971e","is_oa":true,"landing_page_url":"https://doaj.org/article/05f0e5ec5b7e4334958fd9da1e24971e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 24, Iss 9, p 1199 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/24/9/1199/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e24091199","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy; Volume 24; Issue 9; Pages: 1199","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9497468","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9497468","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e24091199","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24091199","pdf_url":"https://www.mdpi.com/1099-4300/24/9/1199/pdf?version=1663734342","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G235930821","display_name":null,"funder_award_id":"4172034","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G2597361322","display_name":null,"funder_award_id":"ZR2020MF019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2821998345","display_name":null,"funder_award_id":"4172034","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G5024062706","display_name":null,"funder_award_id":"4172034","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7319533750","display_name":null,"funder_award_id":"ZR2020MF019","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G7328329340","display_name":null,"funder_award_id":"61871380","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G757016564","display_name":null,"funder_award_id":"61871380","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G77349881","display_name":null,"funder_award_id":"61871380","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8206387859","display_name":null,"funder_award_id":"ZR2020MF019","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null},{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4293530432.pdf","grobid_xml":"https://content.openalex.org/works/W4293530432.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W2035204699","https://openalex.org/W2047781078","https://openalex.org/W2154507364","https://openalex.org/W2333822803","https://openalex.org/W2587828787","https://openalex.org/W2653127109","https://openalex.org/W2767995764","https://openalex.org/W2778593459","https://openalex.org/W2791490164","https://openalex.org/W2861597070","https://openalex.org/W2889609823","https://openalex.org/W2901100349","https://openalex.org/W2902226446","https://openalex.org/W2911604108","https://openalex.org/W2933486688","https://openalex.org/W2962775327","https://openalex.org/W2988147404","https://openalex.org/W3004660995","https://openalex.org/W3018315210","https://openalex.org/W3043823510","https://openalex.org/W3124491097","https://openalex.org/W3182900868","https://openalex.org/W3202201446","https://openalex.org/W3204426737","https://openalex.org/W4205590151","https://openalex.org/W4214918381","https://openalex.org/W4220830918","https://openalex.org/W4221103790","https://openalex.org/W4226078124","https://openalex.org/W4280620890","https://openalex.org/W4283448162","https://openalex.org/W6745990181"],"related_works":["https://openalex.org/W2367921179","https://openalex.org/W3080476861","https://openalex.org/W657288383","https://openalex.org/W2373659438","https://openalex.org/W2102683994","https://openalex.org/W2063813108","https://openalex.org/W2097403386","https://openalex.org/W2050783914","https://openalex.org/W2385310810","https://openalex.org/W2736846486"],"abstract_inverted_index":{"Automated":[0],"segmentation":[1,168,180],"of":[2,16,49,112,132,155],"brain":[3,37,84],"tumors":[4],"is":[5,44,54,101,121,136],"a":[6],"difficult":[7],"procedure":[8],"due":[9],"to":[10,56,63,103,151],"the":[11,17,41,47,58,64,71,80,96,106,118,124,130,133,141,153,156,175],"variability":[12],"and":[13,31,60,86,89,92,115,129,159,165,182],"blurred":[14],"boundary":[15,131],"lesions.":[18],"In":[19],"this":[20],"study,":[21],"we":[22],"propose":[23],"an":[24],"automated":[25],"model":[26,35,120],"based":[27,45],"on":[28,46],"Bendlet":[29,42,52],"transform":[30,53,143],"improved":[32],"Chan-Vese":[33],"(CV)":[34],"for":[36],"tumor":[38,107,134],"segmentation.":[39],"Since":[40],"system":[43],"principle":[48],"sparse":[50],"approximation,":[51],"applied":[55],"describe":[57],"images":[59,62,150],"map":[61],"feature":[65,72],"space":[66],"and,":[67],"thereby,":[68],"first":[69],"obtain":[70],"set.":[73],"This":[74],"can":[75],"help":[76],"in":[77],"effectively":[78],"exploring":[79],"mapping":[81],"relationship":[82],"between":[83],"lesions":[85],"normal":[87],"tissues,":[88],"achieving":[90],"multi-scale":[91],"multi-directional":[93],"registration.":[94],"Secondly,":[95],"SSIM":[97],"region":[98,108,135,166],"detection":[99],"method":[100],"proposed":[102,157,176],"preliminarily":[104],"locate":[105],"from":[109],"three":[110],"aspects":[111],"brightness,":[113],"structure,":[114],"contrast.":[116],"Finally,":[117],"CV":[119],"solved":[122],"by":[123,140],"Hermite-Shannon-Cosine":[125],"wavelet":[126,142],"homotopy":[127],"method,":[128],"more":[137],"accurately":[138],"delineated":[139],"coefficient.":[144],"We":[145],"randomly":[146],"selected":[147],"some":[148],"cross-sectional":[149],"verify":[152],"effectiveness":[154],"algorithm":[158,177],"compared":[160],"with":[161],"CV,":[162],"Ostu,":[163],"K-FCM,":[164],"growing":[167],"methods.":[169],"The":[170],"experimental":[171],"results":[172],"showed":[173],"that":[174],"had":[178],"higher":[179],"accuracy":[181],"better":[183],"stability.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}