{"id":"https://openalex.org/W2790813172","doi":"https://doi.org/10.1117/12.2293677","title":"A new fractional order derivative based active contour model for colon wall segmentation","display_name":"A new fractional order derivative based active contour model for colon wall segmentation","publication_year":2018,"publication_date":"2018-02-27","ids":{"openalex":"https://openalex.org/W2790813172","doi":"https://doi.org/10.1117/12.2293677","mag":"2790813172"},"language":"en","primary_location":{"id":"doi:10.1117/12.2293677","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2293677","pdf_url":null,"source":{"id":"https://openalex.org/S4306519508","display_name":"Medical Imaging 2018: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2018: Computer-Aided Diagnosis","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/A5079702106","display_name":"Lihong C. Li","orcid":null},"institutions":[{"id":"https://openalex.org/I142393192","display_name":"College of Staten Island","ror":"https://ror.org/02p179j44","country_code":"US","type":"education","lineage":["https://openalex.org/I142393192"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lihong C. Li","raw_affiliation_strings":["College of Staten Island (United States)"],"affiliations":[{"raw_affiliation_string":"College of Staten Island (United States)","institution_ids":["https://openalex.org/I142393192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049303906","display_name":"Bo Chen","orcid":"https://orcid.org/0000-0002-6606-431X"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Bo Chen","raw_affiliation_strings":["Shenzhen Univ. (China)","Stony Brook Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Shenzhen Univ. (China)","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Stony Brook Univ. (United States)","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100628383","display_name":"Huafeng Wang","orcid":"https://orcid.org/0000-0002-8267-672X"},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huafeng Wang","raw_affiliation_strings":["North China Univ. of Technology (China)"],"affiliations":[{"raw_affiliation_string":"North China Univ. of Technology (China)","institution_ids":["https://openalex.org/I1456306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101765901","display_name":"Wen-Sheng Chen","orcid":"https://orcid.org/0000-0001-8282-9960"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wensheng Chen","raw_affiliation_strings":["Shenzhen Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Shenzhen Univ. (China)","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110322946","display_name":"Zhengrong Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I1327163397","display_name":"State University of New York","ror":"https://ror.org/01q1z8k08","country_code":"US","type":"education","lineage":["https://openalex.org/I1327163397"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengrong Liang","raw_affiliation_strings":["State Univ. of New York (United States)"],"affiliations":[{"raw_affiliation_string":"State Univ. of New York (United States)","institution_ids":["https://openalex.org/I1327163397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107412076","display_name":"Shan Huang","orcid":"https://orcid.org/0009-0008-2856-5851"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Huang","raw_affiliation_strings":["Shenzhen Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Shenzhen Univ. (China)","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037313481","display_name":"Xinzhou Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I76513827","display_name":"New York City College of Technology","ror":"https://ror.org/021a7pw18","country_code":"US","type":"education","lineage":["https://openalex.org/I76513827"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinzhou Wei","raw_affiliation_strings":["New York City College of Technology (United States)"],"affiliations":[{"raw_affiliation_string":"New York City College of Technology (United States)","institution_ids":["https://openalex.org/I76513827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5079702106"],"corresponding_institution_ids":["https://openalex.org/I142393192"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01572488,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"4","issue":null,"first_page":"42","last_page":"42"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9962000250816345,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9958999752998352,"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/segmentation","display_name":"Segmentation","score":0.7785135507583618},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.62621009349823},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6071251034736633},{"id":"https://openalex.org/keywords/active-contour-model","display_name":"Active contour model","score":0.5046316385269165},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45592382550239563},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4203609526157379},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3902534246444702},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.36738020181655884},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13156113028526306}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7785135507583618},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.62621009349823},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6071251034736633},{"id":"https://openalex.org/C112353826","wikidata":"https://www.wikidata.org/wiki/Q127313","display_name":"Active contour model","level":4,"score":0.5046316385269165},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45592382550239563},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4203609526157379},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3902534246444702},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.36738020181655884},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13156113028526306}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2293677","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2293677","pdf_url":null,"source":{"id":"https://openalex.org/S4306519508","display_name":"Medical Imaging 2018: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2018: Computer-Aided Diagnosis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W267311712","https://openalex.org/W1967186380","https://openalex.org/W1982012787","https://openalex.org/W1993519341","https://openalex.org/W2012350520","https://openalex.org/W2029692362","https://openalex.org/W2046116530","https://openalex.org/W2070559430","https://openalex.org/W2089257548","https://openalex.org/W2111725022","https://openalex.org/W2116040950","https://openalex.org/W2345136208","https://openalex.org/W2380436650","https://openalex.org/W2570618306","https://openalex.org/W2602077962","https://openalex.org/W3211330693","https://openalex.org/W6653376280","https://openalex.org/W6729114209"],"related_works":["https://openalex.org/W2387003628","https://openalex.org/W123102278","https://openalex.org/W2081609930","https://openalex.org/W2365596436","https://openalex.org/W163453029","https://openalex.org/W1522196789","https://openalex.org/W4210537690","https://openalex.org/W2885157826","https://openalex.org/W2159463658","https://openalex.org/W1979702773"],"abstract_inverted_index":{"Segmentation":[0],"of":[1,23,31,34,166,204],"colon":[2,27,59,78,98,173,197],"wall":[3,39,60,99,174],"plays":[4],"an":[5,115],"important":[6],"role":[7],"in":[8,65,136,151],"advancing":[9],"computed":[10],"tomographic":[11],"colonography":[12],"(CTC)":[13],"toward":[14],"a":[15,55,72,85,141],"screening":[16],"modality.":[17],"Due":[18],"to":[19,94,118,155],"the":[20,32,48,96,101,108,119,137,152,157,163,167,188],"low":[21,158],"contrast":[22],"CT":[24],"attenuation":[25],"around":[26],"wall,":[28,198],"accurate":[29],"segmentation":[30,138,169,175],"boundary":[33],"both":[35],"inner":[36],"and":[37,161],"outer":[38],"is":[40,112,132,148,191],"very":[41,192],"challenging.":[42],"In":[43,105],"this":[44,106],"paper,":[45],"based":[46,76,90],"on":[47,179],"geodesic":[49],"active":[50,91],"contour":[51,92],"model,":[52,107],"we":[53],"develop":[54],"new":[56,86,153,168],"model":[57,93,111,121,154],"for":[58],"segmentation.":[61],"First,":[62],"tagged":[63],"materials":[64],"CTC":[66,103,182],"images":[67],"were":[68],"automatically":[69,195],"removed":[70],"via":[71,209],"partial":[73],"volume":[74],"(PV)":[75],"electronic":[77],"cleansing":[79],"(ECC)":[80],"strategy.":[81],"We":[82],"then":[83],"present":[84,189],"fractional":[87,142],"order":[88,143],"derivative":[89,145],"segment":[95],"volumetric":[97],"from":[100],"cleansed":[102],"images.":[104],"regionbased":[109],"Chan-Vese":[110],"incorporated":[113],"as":[114],"energy":[116,146],"term":[117,147],"whole":[120],"so":[122],"that":[123,187],"not":[124],"only":[125],"edge/gradient":[126],"information":[127,131,160],"but":[128],"also":[129,149],"region/volume":[130],"taken":[133],"into":[134],"account":[135],"process.":[139],"Furthermore,":[140],"differentiation":[144],"developed":[150],"preserve":[156],"frequency":[159],"improve":[162],"noise":[164],"immunity":[165],"model.":[170],"The":[171],"proposed":[172],"approach":[176],"was":[177],"validated":[178],"16":[180],"patient":[181],"scans.":[183],"Experimental":[184],"results":[185],"indicate":[186],"scheme":[190],"promising":[193],"towards":[194],"segmenting":[196],"thus":[199],"facilitating":[200],"computer":[201],"aided":[202],"detection":[203],"initial":[205],"colonic":[206],"polyp":[207],"candidates":[208],"CTC.":[210]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
