{"id":"https://openalex.org/W4416251542","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228025","title":"TSNet: A Transformer-based Medical Image Segmentation Algorithm for Improving Channel Interaction","display_name":"TSNet: A Transformer-based Medical Image Segmentation Algorithm for Improving Channel Interaction","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251542","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228025"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228025","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228025","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":null,"display_name":"Hujin Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hujin Peng","raw_affiliation_strings":["Changsha University of Science &#x0026; Technology,School of Computer and Communication Engineering,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Changsha University of Science &#x0026; Technology,School of Computer and Communication Engineering,Changsha,China","institution_ids":["https://openalex.org/I56934997"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069076046","display_name":"Tan Deng","orcid":"https://orcid.org/0000-0003-4945-9974"},"institutions":[{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tan Deng","raw_affiliation_strings":["Changsha University of Science &#x0026; Technology,School of Computer and Communication Engineering,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Changsha University of Science &#x0026; Technology,School of Computer and Communication Engineering,Changsha,China","institution_ids":["https://openalex.org/I56934997"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100662054","display_name":"Zeyu Chen","orcid":"https://orcid.org/0000-0001-6286-0581"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zeyu Chen","raw_affiliation_strings":["Hunan University,College of Computer Science and Electronic Engineering,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Hunan University,College of Computer Science and Electronic Engineering,Changsha,China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009940245","display_name":"Shiyu Mei","orcid":null},"institutions":[{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiyu Mei","raw_affiliation_strings":["Changsha University of Science &#x0026; Technology,School of Computer and Communication Engineering,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Changsha University of Science &#x0026; Technology,School of Computer and Communication Engineering,Changsha,China","institution_ids":["https://openalex.org/I56934997"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108140408","display_name":"Mingfeng Huang","orcid":"https://orcid.org/0000-0002-3741-7550"},"institutions":[{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingfeng Huang","raw_affiliation_strings":["Changsha University of Science &#x0026; Technology,School of Computer and Communication Engineering,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Changsha University of Science &#x0026; Technology,School of Computer and Communication Engineering,Changsha,China","institution_ids":["https://openalex.org/I56934997"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021152658","display_name":"Ronghui Cao","orcid":"https://orcid.org/0000-0001-5026-0001"},"institutions":[{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ronghui Cao","raw_affiliation_strings":["Changsha University of Science &#x0026; Technology,School of Computer and Communication Engineering,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Changsha University of Science &#x0026; Technology,School of Computer and Communication Engineering,Changsha,China","institution_ids":["https://openalex.org/I56934997"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015343555","display_name":"Xiaoyong Tang","orcid":"https://orcid.org/0000-0002-6661-5900"},"institutions":[{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyong Tang","raw_affiliation_strings":["Changsha University of Science &#x0026; Technology,School of Computer and Communication Engineering,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Changsha University of Science &#x0026; Technology,School of Computer and Communication Engineering,Changsha,China","institution_ids":["https://openalex.org/I56934997"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101588404","display_name":"Wenzheng Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzheng Liu","raw_affiliation_strings":["Changsha University of Science &#x0026; Technology,School of Computer and Communication Engineering,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Changsha University of Science &#x0026; Technology,School of Computer and Communication Engineering,Changsha,China","institution_ids":["https://openalex.org/I56934997"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I56934997"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33942762,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.5224999785423279,"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":0.5224999785423279,"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":0.13860000669956207,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.06199999898672104,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6759999990463257},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6123999953269958},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5422999858856201},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5293999910354614},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.47450000047683716},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.4657999873161316},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46540001034736633},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42080000042915344},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.41909998655319214}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7177000045776367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6894999742507935},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6759999990463257},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6123999953269958},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5422999858856201},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5293999910354614},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.47450000047683716},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.4657999873161316},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46540001034736633},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42309999465942383},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42080000042915344},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.41909998655319214},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.39980000257492065},{"id":"https://openalex.org/C141898687","wikidata":"https://www.wikidata.org/wiki/Q1501997","display_name":"Hausdorff distance","level":2,"score":0.3961000144481659},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.39590001106262207},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3634999990463257},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.33899998664855957},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.329800009727478},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.31520000100135803},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3003000020980835},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.295199990272522},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26649999618530273},{"id":"https://openalex.org/C48548287","wikidata":"https://www.wikidata.org/wiki/Q6803557","display_name":"Mean-shift","level":3,"score":0.266400009393692},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.25619998574256897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228025","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228025","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2752782242","https://openalex.org/W2888358068","https://openalex.org/W2996290406","https://openalex.org/W3119205652","https://openalex.org/W3138516171","https://openalex.org/W3153088206","https://openalex.org/W3153148133","https://openalex.org/W3168491317","https://openalex.org/W3203480968","https://openalex.org/W3204255739","https://openalex.org/W3211490618","https://openalex.org/W3212933375","https://openalex.org/W4212875960","https://openalex.org/W4284896652","https://openalex.org/W4285600307","https://openalex.org/W4289752563","https://openalex.org/W4312568229","https://openalex.org/W4319300975","https://openalex.org/W4321232185","https://openalex.org/W4385346076","https://openalex.org/W4386264535","https://openalex.org/W4387430177","https://openalex.org/W4394596865","https://openalex.org/W4402716243","https://openalex.org/W4402754282","https://openalex.org/W4402904115"],"related_works":[],"abstract_inverted_index":{"Medical":[0],"image":[1,40,137],"segmentation":[2,41,172],"is":[3],"crucial":[4],"for":[5,168],"separating":[6],"tissue":[7],"structures":[8],"and":[9,20,48,63,71,94,109,116,122,131,158,170,193],"anatomical":[10],"regions.":[11],"However,":[12],"due":[13,42],"to":[14,43,59,105],"significant":[15],"variations":[16],"in":[17,25,38,134,186],"size,":[18],"shape,":[19],"density":[21],"of":[22,188],"target":[23],"tissues":[24],"medical":[26,39,136],"images,":[27],"this":[28,79],"task":[29],"faces":[30],"many":[31],"challenges.":[32],"Neural":[33,55],"networks":[34],"are":[35],"widely":[36],"used":[37],"their":[44],"powerful":[45],"feature":[46,129],"extraction":[47,130],"pattern":[49],"recognition":[50],"capabilities.":[51],"But":[52],"traditional":[53],"Convolutional":[54],"Networks":[56],"(CNNs)":[57],"struggle":[58],"capture":[60],"long-range":[61],"dependencies,":[62],"Transformer":[64],"models":[65],"may":[66],"lack":[67],"sufficient":[68],"channel":[69,108],"interaction":[70,157],"detail":[72],"representation.":[73],"To":[74],"address":[75],"the":[76,127,140,151,156,176,183,194],"above":[77],"issues,":[78],"paper":[80],"proposes":[81],"a":[82,102],"novel":[83],"architecture":[84],"called":[85],"TSNet,":[86],"which":[87],"innovatively":[88],"integrates":[89],"SimAM":[90,142],"(Neural":[91],"Attention":[92,96,100],"Module)":[93],"Triplet":[95,99],"mechanism.":[97],"First,":[98],"adopts":[101],"three-branch":[103],"structure":[104],"effectively":[106],"encodes":[107],"spatial":[110],"information.":[111],"By":[112],"reducing":[113],"information":[114],"loss":[115],"achieving":[117],"direct":[118],"correspondence":[119],"between":[120,160],"channels":[121],"weights,":[123],"it":[124],"significantly":[125,180],"enhances":[126],"model\u2019s":[128],"representation":[132],"capabilities":[133],"complex":[135],"processing.":[138],"Meanwhile,":[139],"parameter-free":[141],"module":[143],"generates":[144],"adaptive":[145],"3D":[146],"attention":[147],"weights":[148],"by":[149],"optimizing":[150,155],"energy":[152],"function,":[153],"further":[154],"fusion":[159],"features.":[161],"Finally,":[162],"extensive":[163],"experiments":[164],"on":[165],"real":[166],"datasets":[167],"heart":[169],"CT":[171],"have":[173],"shown":[174],"that":[175],"proposed":[177],"TSNet":[178],"performs":[179],"better":[181],"than":[182],"baseline":[184],"method":[185],"terms":[187],"Dice":[189],"Similarity":[190],"Coefficient":[191],"(DSC)":[192],"95th":[195],"percentile":[196],"Hausdorff":[197],"Distance":[198],"(HD95).":[199]},"counts_by_year":[],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-11-14T00:00:00"}
