{"id":"https://openalex.org/W7126023122","doi":"https://doi.org/10.1109/bibm66473.2025.11356293","title":"LPM-Net: Lightweight Periodic Modeling Medical Image Segmentation Network Based on Supervision Strategy","display_name":"LPM-Net: Lightweight Periodic Modeling Medical Image Segmentation Network Based on Supervision Strategy","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126023122","doi":"https://doi.org/10.1109/bibm66473.2025.11356293"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356293","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356293","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5044628469","display_name":"Yanchi Ou","orcid":"https://orcid.org/0000-0002-3196-9266"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanchi Ou","raw_affiliation_strings":["Southwest University of Science and Technology,Mianyang,PR China,621010"],"affiliations":[{"raw_affiliation_string":"Southwest University of Science and Technology,Mianyang,PR China,621010","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010589073","display_name":"Y. Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yufeng Chen","raw_affiliation_strings":["Southwest University of Science and Technology,Mianyang,PR China,621010"],"affiliations":[{"raw_affiliation_string":"Southwest University of Science and Technology,Mianyang,PR China,621010","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100604662","display_name":"Shuai Xu","orcid":"https://orcid.org/0000-0001-9928-5437"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shijie Xu","raw_affiliation_strings":["Southwest University of Science and Technology,Mianyang,PR China,621010"],"affiliations":[{"raw_affiliation_string":"Southwest University of Science and Technology,Mianyang,PR China,621010","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010114011","display_name":"Siyu Chen","orcid":"https://orcid.org/0000-0002-9978-4313"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siyu Chen","raw_affiliation_strings":["Southwest University of Science and Technology,Mianyang,PR China,621010"],"affiliations":[{"raw_affiliation_string":"Southwest University of Science and Technology,Mianyang,PR China,621010","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051074667","display_name":"Xiaoqian Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqian Zhang","raw_affiliation_strings":["Southwest University of Science and Technology,Mianyang,PR China,621010"],"affiliations":[{"raw_affiliation_string":"Southwest University of Science and Technology,Mianyang,PR China,621010","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109987566","display_name":"Jie Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095398","display_name":"Mianyang Central Hospital","ror":"https://ror.org/00s528j33","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210095398"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Lin","raw_affiliation_strings":["Mianyang Central Hospital,Mianyang,China,621000"],"affiliations":[{"raw_affiliation_string":"Mianyang Central Hospital,Mianyang,China,621000","institution_ids":["https://openalex.org/I4210095398"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5044628469"],"corresponding_institution_ids":["https://openalex.org/I1297991670"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.73265219,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3957","last_page":"3962"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.21379999816417694,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.21379999816417694,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.17399999499320984,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.09059999883174896,"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/deep-learning","display_name":"Deep learning","score":0.6704999804496765},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.669700026512146},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5724999904632568},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4726000130176544},{"id":"https://openalex.org/keywords/medical-diagnosis","display_name":"Medical diagnosis","score":0.40369999408721924},{"id":"https://openalex.org/keywords/network-model","display_name":"Network model","score":0.38440001010894775},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.38029998540878296}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6879000067710876},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6704999804496765},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.669700026512146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5819000005722046},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5724999904632568},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4726000130176544},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4691999852657318},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.40369999408721924},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.38440001010894775},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.38029998540878296},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3725000023841858},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.367900013923645},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3594000041484833},{"id":"https://openalex.org/C32946077","wikidata":"https://www.wikidata.org/wiki/Q618079","display_name":"Network analysis","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C21338462","wikidata":"https://www.wikidata.org/wiki/Q1662581","display_name":"Information model","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2935999929904938},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2757999897003174},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356293","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356293","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2744692634","https://openalex.org/W2963946669","https://openalex.org/W3034328552","https://openalex.org/W3197957534","https://openalex.org/W4295934721","https://openalex.org/W4297238433","https://openalex.org/W4323897048","https://openalex.org/W4386561400","https://openalex.org/W4386913388","https://openalex.org/W4388756587","https://openalex.org/W4390738634","https://openalex.org/W4401481079","https://openalex.org/W4406260608","https://openalex.org/W4406262102"],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,8,48,53,81,84,89,97,101,107,132,156,176,179],"continuous":[2],"progress":[3],"of":[4,10,19,165,178],"medical":[5,20,30],"technology":[6],"and":[7,25,35,87,163],"improvement":[9],"public":[11],"health":[12],"awareness,":[13],"people's":[14],"requirements":[15],"for":[16,120,136],"accurate":[17],"analysis":[18,162],"images":[21,31],"are":[22,39],"becoming":[23],"more":[24,26],"stringent.":[27],"However,":[28],"most":[29],"have":[32],"unclear":[33],"boundaries,":[34],"deep":[36,108,160],"learning":[37,109,164],"networks":[38],"prone":[40],"to":[41,91,99,130,158],"\u201clearning":[42,93],"inertia\u201d":[43],"during":[44],"training,":[45],"which":[46,123,148],"affects":[47],"segmentation":[49],"effect.":[50],"To":[51,174],"address":[52],"above":[54],"issues,":[55],"we":[56,185],"propose":[57],"an":[58],"innovative":[59],"Lightweight":[60],"Periodic":[61,141],"Modeling":[62,143],"Medical":[63],"Image":[64],"Segmentation":[65],"Network":[66],"Based":[67],"on":[68,190],"Supervision":[69],"Strategy":[70,78],"(LPM-Net).":[71],"In":[72,113,128],"particular,":[73],"Deep":[74],"Adaptive":[75],"Weight":[76],"Allocation":[77],"(DAWAS)":[79],"guides":[80],"network":[82,90,98,125,133,161],"in":[83,182],"right":[85],"direction":[86],"monitors":[88],"prevent":[92],"inertia\u201d.":[94],"This":[95,153],"helps":[96],"update":[100],"weight":[102],"information":[103,111,168],"as":[104,106],"well":[105],"feature":[110,167],"efficiently.":[112],"addition,":[114],"FAN":[115],"Conv":[116],"uses":[117],"Fourier":[118],"poles":[119],"periodic":[121,171],"modeling,":[122],"improves":[124],"modeling":[126,139,172],"capabilities.":[127],"order":[129],"improve":[131],"even":[134],"further":[135],"mining":[137],"hidden":[138],"information,":[140],"Implicit":[142],"Module":[144],"(PIMM)":[145],"is":[146,149,195],"proposed,":[147],"extended":[150],"by":[151],"FANConv.":[152],"module":[154],"has":[155],"ability":[157],"facilitate":[159],"potential":[166],"along":[169],"with":[170],"capability.":[173],"verify":[175],"superiority":[177],"method":[180],"proposed":[181],"this":[183],"paper,":[184],"conducted":[186],"thorough":[187],"experimental":[188],"verifications":[189],"three":[191],"datasets.":[192],"Our":[193],"code":[194],"available":[196],"at":[197],"https://github.com/ououyyILPM_Net.":[198]},"counts_by_year":[],"updated_date":"2026-02-23T20:09:44.859080","created_date":"2026-01-30T00:00:00"}