{"id":"https://openalex.org/W4416251310","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228985","title":"VMC-UNet: A U-shaped structure combining Mamba and CNN for medical image segmentation","display_name":"VMC-UNet: A U-shaped structure combining Mamba and CNN for medical image segmentation","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251310","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228985"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228985","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5107388049","display_name":"Heng Li","orcid":"https://orcid.org/0000-0002-9270-6304"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haocun Li","raw_affiliation_strings":["College of Mathematics and System Sciences Xinjiang University,Urumqi,China"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and System Sciences Xinjiang University,Urumqi,China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082289322","display_name":"Kaiyan Song","orcid":"https://orcid.org/0000-0001-9022-2376"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaiyan Song","raw_affiliation_strings":["College of Mathematics and System Sciences Xinjiang University,Urumqi,China"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and System Sciences Xinjiang University,Urumqi,China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100405787","display_name":"Ping Zhang","orcid":"https://orcid.org/0000-0002-0269-104X"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Zhang","raw_affiliation_strings":["College of Mathematics and System Sciences Xinjiang University,Urumqi,China"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and System Sciences Xinjiang University,Urumqi,China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023489620","display_name":"Haizheng Yu","orcid":"https://orcid.org/0000-0001-5529-7698"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haizheng Yu","raw_affiliation_strings":["College of Mathematics and System Sciences Xinjiang University,Urumqi,China"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and System Sciences Xinjiang University,Urumqi,China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111806638","display_name":"Hong Bian","orcid":null},"institutions":[{"id":"https://openalex.org/I1334729051","display_name":"Xinjiang Normal University","ror":"https://ror.org/00ndrvk93","country_code":"CN","type":"education","lineage":["https://openalex.org/I1334729051"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Bian","raw_affiliation_strings":["School of Mathematical Sciences Xinjiang Normal University,Urumqi,China"],"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences Xinjiang Normal University,Urumqi,China","institution_ids":["https://openalex.org/I1334729051"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5107388049"],"corresponding_institution_ids":["https://openalex.org/I96908189"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.48822394,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.7003999948501587,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.7003999948501587,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.1606999933719635,"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":0.020999999716877937,"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":0.7346000075340271},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6227999925613403},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6159999966621399},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6003999710083008},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5422999858856201},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5078999996185303},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.4657000005245209}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7346000075340271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7314000129699707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7303000092506409},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6227999925613403},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6159999966621399},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6003999710083008},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5422999858856201},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5078999996185303},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.4657000005245209},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4449000060558319},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42829999327659607},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.37599998712539673},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35670000314712524},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30230000615119934},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.2655999958515167}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228985","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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":26,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2104636679","https://openalex.org/W2194775991","https://openalex.org/W2341106171","https://openalex.org/W2601564443","https://openalex.org/W2884436604","https://openalex.org/W2923997689","https://openalex.org/W2962914239","https://openalex.org/W2963446712","https://openalex.org/W2963946669","https://openalex.org/W3138516171","https://openalex.org/W3197957534","https://openalex.org/W3203497085","https://openalex.org/W3204166336","https://openalex.org/W3212933375","https://openalex.org/W4289752563","https://openalex.org/W4296425595","https://openalex.org/W4312794844","https://openalex.org/W4313527340","https://openalex.org/W4321232185","https://openalex.org/W4385245566","https://openalex.org/W4386075572","https://openalex.org/W4400519485","https://openalex.org/W4414243662","https://openalex.org/W6902762063"],"related_works":[],"abstract_inverted_index":{"In":[0,22],"medical":[1,33,169],"image":[2,34,170],"segmentation":[3,112,163,171],"tasks,":[4,172],"convolutional":[5],"neural":[6],"networks":[7],"(CNNs)":[8],"have":[9,28,82],"been":[10],"extensively":[11],"employed":[12],"due":[13],"to":[14,18,40],"their":[15,37,67],"exceptional":[16],"ability":[17],"extract":[19],"local":[20,105,143],"features.":[21],"recent":[23],"years,":[24],"Vision":[25],"Transformers":[26],"(ViTs)":[27],"also":[29],"gained":[30],"prominence":[31],"in":[32,49,58,64,69,87,101,162],"segmentation,":[35],"leveraging":[36],"powerful":[38],"capacity":[39],"model":[41,131],"long-range":[42,89],"dependencies.":[43],"However,":[44],"CNNs":[45],"encounter":[46],"significant":[47,160],"limitations":[48],"capturing":[50,103],"global":[51,135],"dependency":[52],"information,":[53],"while":[54],"the":[55,133,141],"quadratic":[56],"growth":[57],"computational":[59,93],"complexity":[60],"with":[61,91,140],"sequence":[62],"length":[63],"ViTs":[65],"hampers":[66],"efficiency":[68],"practical":[70],"applications.To":[71],"address":[72],"this":[73,96,118],"bottleneck,":[74],"state":[75],"space":[76],"models":[77],"(SSMs),":[78],"such":[79],"as":[80],"Mamba,":[81],"recently":[83],"demonstrated":[84],"remarkable":[85],"performance":[86],"modeling":[88,136],"dependencies":[90],"linear":[92],"complexity.":[94],"Despite":[95],"advantage,":[97],"Mamba":[98,139],"faces":[99],"challenges":[100],"effectively":[102],"fine-grained":[104],"features,":[106],"which":[107],"are":[108],"essential":[109],"for":[110],"high-precision":[111],"tasks.":[113],"To":[114],"overcome":[115],"these":[116],"challenges,":[117],"paper":[119],"introduces":[120],"a":[121,150],"novel":[122],"dual-stream":[123],"U-shaped":[124],"network":[125],"architecture,":[126],"termed":[127],"VMC-UNet.":[128],"The":[129],"proposed":[130],"integrates":[132],"efficient":[134],"capabilities":[137],"of":[138,147],"precise":[142],"feature":[144],"extraction":[145],"strengths":[146],"CNNs,":[148],"offering":[149],"balanced":[151],"and":[152,165,175],"effective":[153],"solution.Experimental":[154],"results":[155],"reveal":[156],"that":[157],"VMC-UNet":[158],"achieves":[159],"improvements":[161],"accuracy":[164],"robustness":[166],"across":[167],"various":[168],"including":[173],"organ":[174],"skin":[176],"lesion":[177],"segmentation.":[178],".":[179]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}