{"id":"https://openalex.org/W4405334210","doi":"https://doi.org/10.1137/24m1633868","title":"Regularized CNN with Geodesic Active Contour and Edge Predictor for Image Segmentation","display_name":"Regularized CNN with Geodesic Active Contour and Edge Predictor for Image Segmentation","publication_year":2024,"publication_date":"2024-12-12","ids":{"openalex":"https://openalex.org/W4405334210","doi":"https://doi.org/10.1137/24m1633868"},"language":"en","primary_location":{"id":"doi:10.1137/24m1633868","is_oa":false,"landing_page_url":"https://doi.org/10.1137/24m1633868","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","raw_type":"journal-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/A5100539659","display_name":"Zhengmeng Jin","orcid":"https://orcid.org/0000-0002-8627-3741"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengmeng Jin","raw_affiliation_strings":["School of Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, 210003, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, 210003, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116592778","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0003-2227-075X"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wang","raw_affiliation_strings":["School of Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, 210003, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, 210003, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010561682","display_name":"Michael K. Ng","orcid":"https://orcid.org/0000-0001-6833-5227"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Michael K. Ng","raw_affiliation_strings":["Department of Mathematics, Hong Kong Baptist University, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Hong Kong Baptist University, Hong Kong","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063992856","display_name":"Lihua Min","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lihua Min","raw_affiliation_strings":["Corresponding author. School of Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, 210003, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Corresponding author. School of Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, 210003, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1545,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.46625965,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"17","issue":"4","first_page":"2392","last_page":"2417"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9965000152587891,"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":0.9955000281333923,"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/geodesic","display_name":"Geodesic","score":0.7911157608032227},{"id":"https://openalex.org/keywords/active-contour-model","display_name":"Active contour model","score":0.7236326932907104},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6783531904220581},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6045256853103638},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5211377143859863},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5165438055992126},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5127931237220764},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5033525824546814},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.4853002429008484},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.48113930225372314},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47968602180480957},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44834890961647034},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.325023889541626},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.21139806509017944}],"concepts":[{"id":"https://openalex.org/C165818556","wikidata":"https://www.wikidata.org/wiki/Q213488","display_name":"Geodesic","level":2,"score":0.7911157608032227},{"id":"https://openalex.org/C112353826","wikidata":"https://www.wikidata.org/wiki/Q127313","display_name":"Active contour model","level":4,"score":0.7236326932907104},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6783531904220581},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6045256853103638},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5211377143859863},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5165438055992126},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5127931237220764},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5033525824546814},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.4853002429008484},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.48113930225372314},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47968602180480957},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44834890961647034},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.325023889541626},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.21139806509017944}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/24m1633868","is_oa":false,"landing_page_url":"https://doi.org/10.1137/24m1633868","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5077780931","display_name":null,"funder_award_id":"12271262","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G651517658","display_name":null,"funder_award_id":"KYCX24-1122","funder_id":"https://openalex.org/F4320321605","funder_display_name":"Government of Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1480714962","https://openalex.org/W1909740415","https://openalex.org/W2044025718","https://openalex.org/W2080622120","https://openalex.org/W2104095591","https://openalex.org/W2104958086","https://openalex.org/W2114487471","https://openalex.org/W2116040950","https://openalex.org/W2142641029","https://openalex.org/W2144751639","https://openalex.org/W2146818756","https://openalex.org/W2153431772","https://openalex.org/W2159152281","https://openalex.org/W2159793005","https://openalex.org/W2404618390","https://openalex.org/W2484752968","https://openalex.org/W2555096873","https://openalex.org/W2907824800","https://openalex.org/W2964227007","https://openalex.org/W3000277488","https://openalex.org/W3014974815","https://openalex.org/W3034167473","https://openalex.org/W3035665735","https://openalex.org/W3042143729","https://openalex.org/W3084350493","https://openalex.org/W3112701542","https://openalex.org/W3193226848","https://openalex.org/W3194662286","https://openalex.org/W3211330693","https://openalex.org/W4200633637","https://openalex.org/W4224024937","https://openalex.org/W4226502176","https://openalex.org/W4392550756"],"related_works":["https://openalex.org/W1978591761","https://openalex.org/W2006673626","https://openalex.org/W185820115","https://openalex.org/W2384347880","https://openalex.org/W2885157826","https://openalex.org/W2159463658","https://openalex.org/W4388208420","https://openalex.org/W2116510815","https://openalex.org/W17460865","https://openalex.org/W2372578044"],"abstract_inverted_index":{"Abstract.":[0],"In":[1],"order":[2],"to":[3,46,74,109,125],"exploit":[4],"effectively":[5],"the":[6,53,58,65,76,91,97,112,136,153,160],"benefits":[7],"of":[8,78,90],"classical":[9],"variational":[10,49,117],"methods":[11,164],"with":[12,159,170],"good":[13],"interpretability":[14],"and":[15,35,81,114,119,148],"high":[16],"generalization":[17],"performance,":[18],"this":[19],"paper":[20],"proposes":[21],"a":[22,48],"novel":[23],"regularized":[24],"convolutional":[25],"neural":[26],"network":[27],"(CNN)":[28],"based":[29,116],"on":[30,145],"geodesic":[31],"active":[32],"contour":[33],"(GAC)":[34],"edge":[36,69,83,93],"predictor":[37,70,84],"(EP)":[38],"for":[39],"image":[40],"segmentation.":[41],"The":[42],"main":[43],"idea":[44],"is":[45,61,72,87,107,132,139,156],"establish":[47],"problem":[50],"which":[51],"integrates":[52],"Heaviside":[54],"function":[55,85,95],"such":[56],"that":[57,135,152],"GAC":[59,113],"prior":[60],"easily":[62],"added":[63],"into":[64,121],"problem.":[66],"Furthermore,":[67],"an":[68,82,100,122],"module":[71,105],"designed":[73],"predict":[75],"edges":[77],"target":[79],"objects":[80],"(EPF)":[86],"generated":[88],"instead":[89],"traditional":[92],"indicator":[94],"in":[96,166],"GAC.":[98],"Besides,":[99],"iterative":[101],"convolution":[102],"soft":[103],"thresholding":[104],"(ICSTM)":[106],"developed":[108],"numerically":[110],"solve":[111],"EPF":[115],"problem,":[118],"merged":[120],"existing":[123],"CNN":[124],"generate":[126],"our":[127],"new":[128],"end-to-end":[129],"network.":[130],"It":[131],"also":[133],"proved":[134],"ICSTM":[137],"algorithm":[138],"unconditionally":[140],"stable.":[141],"Finally,":[142],"experimental":[143],"results":[144],"synthetic,":[146],"MRI":[147],"CT":[149],"images":[150,169],"show":[151],"proposed":[154],"method":[155],"quite":[157],"competitive":[158],"other":[161],"state-of-the-art":[162],"segmentation":[163],"especially":[165],"segmenting":[167],"noisy":[168],"low":[171],"contrast.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-22T07:34:49.880490","created_date":"2025-10-10T00:00:00"}
