{"id":"https://openalex.org/W4415047693","doi":"https://doi.org/10.23919/ccc64809.2025.11179443","title":"A Medical Image Segmentation Method Based on ML-SPCNN","display_name":"A Medical Image Segmentation Method Based on ML-SPCNN","publication_year":2025,"publication_date":"2025-07-28","ids":{"openalex":"https://openalex.org/W4415047693","doi":"https://doi.org/10.23919/ccc64809.2025.11179443"},"language":"en","primary_location":{"id":"doi:10.23919/ccc64809.2025.11179443","doi":"https://doi.org/10.23919/ccc64809.2025.11179443","is_oa":false,"landing_page_url":"https://doi.org/10.23919/ccc64809.2025.11179443","pdf_url":null,"source":{"id":"https://openalex.org/S4363607703","display_name":"Chinese Control Conference (CCC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 44th Chinese Control Conference (CCC)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5101513130","display_name":"Jiaqi Zheng","orcid":"https://orcid.org/0000-0001-8403-9655","observed_orcids":["https://orcid.org/0000-0001-8403-9655","https://orcid.org/0009-0009-6454-3307"]},"institutions":[{"id":"https://openalex.org/I3133134087","display_name":"Lanzhou Jiaotong University","ror":"https://ror.org/03144pv92","country_code":"CN","type":"education","lineage":["https://openalex.org/I3133134087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Zheng","raw_affiliation_strings":["School of Electronic and Information Engineering, Lanzhou Jiaotong University,Lanzhou,China,730070"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Lanzhou Jiaotong University,Lanzhou,China,730070","institution_ids":["https://openalex.org/I3133134087"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jing Lian","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I3133134087","display_name":"Lanzhou Jiaotong University","ror":"https://ror.org/03144pv92","country_code":"CN","type":"education","lineage":["https://openalex.org/I3133134087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Lian","raw_affiliation_strings":["School of Electronic and Information Engineering, Lanzhou Jiaotong University,Lanzhou,China,730070"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Lanzhou Jiaotong University,Lanzhou,China,730070","institution_ids":["https://openalex.org/I3133134087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023370349","display_name":"Jizhao Liu","orcid":"https://orcid.org/0000-0002-8303-2619","observed_orcids":["https://orcid.org/0000-0002-8303-2619"]},"institutions":[{"id":"https://openalex.org/I3133134087","display_name":"Lanzhou Jiaotong University","ror":"https://ror.org/03144pv92","country_code":"CN","type":"education","lineage":["https://openalex.org/I3133134087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jizhao Liu","raw_affiliation_strings":["School of Electronic and Information Engineering, Lanzhou Jiaotong University,Lanzhou,China,730070"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Lanzhou Jiaotong University,Lanzhou,China,730070","institution_ids":["https://openalex.org/I3133134087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103176699","display_name":"Chengzhi Lu","orcid":"https://orcid.org/0000-0002-6421-3828","observed_orcids":["https://orcid.org/0000-0002-6421-3828"]},"institutions":[{"id":"https://openalex.org/I3133134087","display_name":"Lanzhou Jiaotong University","ror":"https://ror.org/03144pv92","country_code":"CN","type":"education","lineage":["https://openalex.org/I3133134087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengzhi Lu","raw_affiliation_strings":["School of Electronic and Information Engineering, Lanzhou Jiaotong University,Lanzhou,China,730070"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Lanzhou Jiaotong University,Lanzhou,China,730070","institution_ids":["https://openalex.org/I3133134087"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048353101","display_name":"Xiangzi Zhang","orcid":"https://orcid.org/0000-0001-7971-0758","observed_orcids":["https://orcid.org/0000-0001-7971-0758"]},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangzi Zhang","raw_affiliation_strings":["School of Psychology, Northwest Normal University,Lanzhou,China,730070"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Psychology, Northwest Normal University,Lanzhou,China,730070","institution_ids":["https://openalex.org/I68986083"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24959498,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"9256","last_page":"9261"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9887999892234802,"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":0.9887999892234802,"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":0.008100000210106373,"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":0.0006000000284984708,"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/medical-image-segmentation","display_name":"medical image segmentation","score":0.996999979019165},{"id":"https://openalex.org/keywords/pulse-coupled-neural-network","display_name":"pulse coupled neural network","score":0.9470000267028809},{"id":"https://openalex.org/keywords/brain-tissue-segmentation","display_name":"brain tissue segmentation","score":0.6890000104904175},{"id":"https://openalex.org/keywords/liver-lesion-segmentation","display_name":"liver lesion segmentation","score":0.996999979019165},{"id":"https://openalex.org/keywords/dynamic-threshold-adjustment","display_name":"dynamic threshold adjustment","score":0.8169999718666077},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"feature extraction","score":0.7149999737739563},{"id":"https://openalex.org/keywords/biologically-inspired-neural-networks","display_name":"biologically inspired neural networks","score":0.6740000247955322}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7889000177383423},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.723800003528595},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6449000239372253},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6448000073432922},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5870000123977661},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5763999819755554},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5649999976158142},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47769999504089355},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.47589999437332153},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4577000141143799},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45489999651908875},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4223000109195709},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3968999981880188},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.36250001192092896},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3467999994754791},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.3273000121116638},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3228999972343445},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.2597000002861023}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/ccc64809.2025.11179443","doi":"https://doi.org/10.23919/ccc64809.2025.11179443","is_oa":false,"landing_page_url":"https://doi.org/10.23919/ccc64809.2025.11179443","pdf_url":null,"source":{"id":"https://openalex.org/S4363607703","display_name":"Chinese Control Conference (CCC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 44th Chinese Control Conference (CCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6240000128746033,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G5652841737","display_name":null,"funder_award_id":"82260364","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2109701261","https://openalex.org/W2908121769","https://openalex.org/W2990875179","https://openalex.org/W3092762625","https://openalex.org/W4285105866","https://openalex.org/W4312019812","https://openalex.org/W4321073115","https://openalex.org/W4391693732","https://openalex.org/W4400828217","https://openalex.org/W4403087785","https://openalex.org/W4403602946","https://openalex.org/W4405105945","https://openalex.org/W4407097708"],"related_works":["https://openalex.org/W7171376416","https://openalex.org/W4415881870","https://openalex.org/W4400828783","https://openalex.org/W4400828167","https://openalex.org/W4415047788","https://openalex.org/W4415049255","https://openalex.org/W4415047898","https://openalex.org/W4400828217","https://openalex.org/W7171457449","https://openalex.org/W7171368981"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,28],"deep":[3],"learning":[4],"have":[5,24],"significantly":[6],"accelerated":[7],"the":[8,66,77,159,162],"progress":[9],"of":[10,19,161],"medical":[11,132,174],"image":[12,175],"analysis.":[13,176],"Among":[14],"these":[15,61],"advances,":[16],"enhanced":[17],"variants":[18],"pulse-coupled":[20],"neural":[21],"networks":[22],"(PCNNs)":[23],"demonstrated":[25],"remarkable":[26],"performance":[27],"complex":[29],"segmentation":[30,104],"tasks,":[31],"owing":[32],"to":[33,53,123],"their":[34],"biologically":[35],"inspired":[36],"mechanisms.":[37],"Nevertheless,":[38],"accurately":[39],"segmenting":[40],"brain":[41],"tissues,":[42],"pancreatic":[43],"structures,":[44],"and":[45,56,168],"liver":[46],"lesions":[47],"remains":[48],"a":[49,106,117,166],"challenging":[50],"task":[51],"due":[52],"ambiguous":[54],"boundaries":[55],"structural":[57],"complexity.":[58],"To":[59],"address":[60],"challenges,":[62],"this":[63],"paper":[64],"proposes":[65],"Mind-Linked":[67],"Simplified":[68],"Pulse-Coupled":[69,81],"Neural":[70,82],"Network":[71,83],"(ML-SPCNN)-an":[72],"innovative":[73],"framework":[74,164],"built":[75],"upon":[76],"Fully":[78],"Convolutional":[79],"Multi-Scale":[80],"(FCMSPCNN).":[84],"The":[85],"proposed":[86,163],"method":[87,138],"introduces":[88],"three":[89],"key":[90],"contributions:(1)":[91],"an":[92,148],"optimized":[93],"dynamic":[94],"threshold":[95],"adjustment":[96],"mechanism":[97],"that":[98,111,136],"reduces":[99],"parameter":[100],"redundancy":[101],"while":[102,152],"enhancing":[103],"stability;(2)":[105],"spatial":[107],"correlation":[108],"enhancement":[109],"strategy":[110],"reinforces":[112],"local":[113],"neuronal":[114],"interactions;":[115],"and(3)":[116],"refined":[118],"feature":[119],"extraction":[120],"module":[121],"designed":[122],"improve":[124],"finestructure":[125],"identification.":[126],"Extensive":[127],"experiments":[128],"conducted":[129],"on":[130],"multiple":[131],"imaging":[133],"datasets":[134],"demonstrate":[135],"our":[137],"outperforms":[139],"state-of-theart":[140],"approaches,":[141],"improving":[142],"lesion":[143],"boundary":[144],"localization":[145],"accuracy":[146],"by":[147],"average":[149],"of$12.7":[150],"\\%(\\mathrm{p}<0.01)$,":[151],"maintaining":[153],"computational":[154],"efficiency.":[155],"These":[156],"results":[157],"highlight":[158],"potential":[160],"as":[165],"robust":[167],"clinically":[169],"viable":[170],"solution":[171],"for":[172],"automated":[173]},"counts_by_year":[],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2025-10-11T00:00:00"}
