{"id":"https://openalex.org/W4327520773","doi":"https://doi.org/10.1145/3574198.3574202","title":"Multi-modal Brain Image Segmentation Based on Multi-Encoder with Hybrid Lateral Connection (MEHLC-Net)","display_name":"Multi-modal Brain Image Segmentation Based on Multi-Encoder with Hybrid Lateral Connection (MEHLC-Net)","publication_year":2022,"publication_date":"2022-11-10","ids":{"openalex":"https://openalex.org/W4327520773","doi":"https://doi.org/10.1145/3574198.3574202"},"language":"en","primary_location":{"id":"doi:10.1145/3574198.3574202","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1145/3574198.3574202","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3574198.3574202?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 9th International Conference on Biomedical and Bioinformatics Engineering","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3574198.3574202?download=true","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071770972","display_name":"Zhengfeng Bao","orcid":"https://orcid.org/0000-0002-7153-0514"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhengfeng Bao","raw_affiliation_strings":["Key Lab of Ubiquitous Network of Ministry of Education, Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Key Lab of Ubiquitous Network of Ministry of Education, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073301632","display_name":"Yiping Wang","orcid":"https://orcid.org/0000-0001-8793-1526"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiping Wang","raw_affiliation_strings":["Key Lab of Ubiquitous Network of Ministry of Education, Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Key Lab of Ubiquitous Network of Ministry of Education, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035627392","display_name":"Jinguo Huang","orcid":"https://orcid.org/0000-0002-6865-2641"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinguo Huang","raw_affiliation_strings":["Key Lab of Ubiquitous Network of Ministry of Education, Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Key Lab of Ubiquitous Network of Ministry of Education, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085386009","display_name":"Guixia Kang","orcid":"https://orcid.org/0000-0002-4039-4505"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guixia Kang","raw_affiliation_strings":["Key Lab of Ubiquitous Network of Ministry of Education, Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Key Lab of Ubiquitous Network of Ministry of Education, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5071770972"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22329029,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"39","issue":null,"first_page":"22","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7666283845901489},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.7387559413909912},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.621568500995636},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6156810522079468},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5745590925216675},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.5694018602371216},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5654670000076294},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5459522008895874},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4605826735496521},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3870267868041992}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7666283845901489},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.7387559413909912},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.621568500995636},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6156810522079468},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5745590925216675},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5694018602371216},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5654670000076294},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5459522008895874},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4605826735496521},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3870267868041992},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3574198.3574202","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1145/3574198.3574202","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3574198.3574202?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 9th International Conference on Biomedical and Bioinformatics Engineering","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3574198.3574202","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1145/3574198.3574202","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3574198.3574202?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 9th International Conference on Biomedical and Bioinformatics Engineering","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.4300000071525574}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2376276132","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G2974758149","display_name":null,"funder_award_id":"82030037","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3660072654","display_name":null,"funder_award_id":"2020XD-A06-1","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","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"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4327520773.pdf","grobid_xml":"https://content.openalex.org/works/W4327520773.grobid-xml"},"referenced_works_count":9,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2565639579","https://openalex.org/W2608353599","https://openalex.org/W2752782242","https://openalex.org/W2895328943","https://openalex.org/W2963446712","https://openalex.org/W2970546341","https://openalex.org/W3101310341","https://openalex.org/W3106286734"],"related_works":["https://openalex.org/W1669643531","https://openalex.org/W2122581818","https://openalex.org/W2159066190","https://openalex.org/W2739874619","https://openalex.org/W2117933325","https://openalex.org/W2110230079","https://openalex.org/W2117664411","https://openalex.org/W1721780360","https://openalex.org/W1507266234","https://openalex.org/W1967061043"],"abstract_inverted_index":{"The":[0],"imaging":[1],"data":[2,206],"of":[3,16,36,90,100,123,163,178,196,208,220],"Multi-modal":[4],"brain":[5],"has":[6],"been":[7],"put":[8],"to":[9,74,170,192],"a":[10,27,113,139],"wide":[11],"use":[12,89,158],"in":[13,44,65,166],"the":[14,37,45,51,55,62,66,76,80,83,88,91,97,101,106,109,121,167,176,194,197,204,212,218,221,227],"identification":[15],"epilepsy":[17],"and":[18,226],"tumor":[19,154],"lesions":[20],"because":[21],"it":[22,71],"can":[23,94,174],"provide":[24],"multi-information":[25],"about":[26],"target":[28],"(epilepsy":[29],"lesion,":[30],"tumor,":[31],"or":[32],"tissue).":[33],"However,":[34],"most":[35],"existing":[38,46],"multi-modal":[39,47,63,152],"medical":[40],"image":[41],"segmentation":[42,48,141],"networks":[43],"schemes,":[49],"on":[50,144,203],"one":[52],"hand,":[53,82],"adopt":[54],"input-level":[56],"fusion":[57,85,181],"strategy,":[58],"which":[59,173],"directly":[60],"integrates":[61],"images":[64,146],"original":[67],"input":[68],"space.":[69],"But":[70],"is":[72],"hard":[73],"preserve":[75],"modality-specific":[77],"properties.":[78],"On":[79],"other":[81,124],"decision-level":[84],"method":[86,202],"with":[87,105,120,133,147,189,211],"single":[92,114],"network":[93,142],"better":[95],"exploit":[96],"unique":[98],"information":[99],"corresponding":[102],"modality,":[103],"but":[104],"problem":[107],"that":[108],"features":[110,122],"learned":[111],"from":[112],"modality":[115],"cannot":[116],"be":[117],"easily":[118],"combined":[119],"modality.":[125],"In":[126],"this":[127],"paper,":[128],"we":[129],"have":[130],"proposed":[131],"Multi-Encoder":[132],"Hybrid":[134],"Lateral":[135],"Connection":[136],"Network":[137],"(MEHLC-Net),":[138],"semantic":[140],"based":[143],"2D":[145],"multi":[148],"encoder":[149],"structure":[150,169],"for":[151],"MRI":[153],"sub-region":[155],"segmentation.":[156],"We":[157,186,199],"hybrid":[159],"lateral":[160],"connections":[161,165],"instead":[162],"long":[164],"U-Net":[168],"extract":[171],"features,":[172],"overcome":[175],"difficulty":[177],"highorder":[179],"feature":[180],"caused":[182],"by":[183,224,230],"multiple":[184],"encoders.":[185],"combine":[187],"cross-connection":[188],"self-attention":[190],"mechanisms":[191],"enhance":[193],"accuracy":[195],"network.":[198],"evaluate":[200],"our":[201,215],"multimodal":[205],"set":[207],"BRATS.":[209],"Compared":[210],"advanced":[213],"No-New-Net,":[214],"model":[216],"improves":[217],"TC":[219],"DSC":[222],"indicator":[223,229],"0.13%":[225],"ET":[228],"0.58%":[231],"respectively.":[232]},"counts_by_year":[],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-10T00:00:00"}
