iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://api.openalex.org/works/doi:10.1007/978-981-99-8558-6_30
{"id":"https://openalex.org/W4390191237","doi":"https://doi.org/10.1007/978-981-99-8558-6_30","title":"PAT-Unet: Paired Attention Transformer for Efficient and Accurate Segmentation of 3D Medical Images","display_name":"PAT-Unet: Paired Attention Transformer for Efficient and Accurate Segmentation of 3D Medical Images","publication_year":2023,"publication_date":"2023-12-25","ids":{"openalex":"https://openalex.org/W4390191237","doi":"https://doi.org/10.1007/978-981-99-8558-6_30"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-981-99-8558-6_30","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"book-chapter","type_crossref":"book-chapter","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/A5020611791","display_name":"Qingzhi Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingzhi Zou","raw_affiliation_strings":["Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102993611","display_name":"Jing Zhao","orcid":"https://orcid.org/0000-0002-8169-2867"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Zhao","raw_affiliation_strings":["Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100351468","display_name":"Ming Li","orcid":"https://orcid.org/0000-0002-7852-0159"},"institutions":[{"id":"https://openalex.org/I134738993","display_name":"Shandong University of Traditional Chinese Medicine","ror":"https://ror.org/0523y5c19","country_code":"CN","type":"education","lineage":["https://openalex.org/I134738993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Li","raw_affiliation_strings":["School of Intelligence and Information Engineering, Shandong University of Traditional Chinese Medicine, Jinan, China"],"affiliations":[{"raw_affiliation_string":"School of Intelligence and Information Engineering, Shandong University of Traditional Chinese Medicine, Jinan, China","institution_ids":["https://openalex.org/I134738993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101924090","display_name":"Lin Yuan","orcid":"https://orcid.org/0000-0002-9694-8191"},"institutions":[{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Yuan","raw_affiliation_strings":["Shandong Engineering Research Center of Big Data Applied Technology, Faculty of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China"],"affiliations":[{"raw_affiliation_string":"Shandong Engineering Research Center of Big Data Applied Technology, Faculty of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China","institution_ids":["https://openalex.org/I4210142748","https://openalex.org/I152269853"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392,"provenance":"doaj"},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":70},"biblio":{"volume":null,"issue":null,"first_page":"358","last_page":"369"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Deep Learning in Computer Vision and Image Recognition","score":0.9998,"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":"Deep Learning in Computer Vision and Image Recognition","score":0.9998,"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/T12422","display_name":"Radiomics in Medical Imaging Analysis","score":0.9986,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T14510","display_name":"Automated Spine Segmentation and Identification","score":0.9973,"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/medical-image-analysis","display_name":"Medical Image Analysis","score":0.517764},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical Imaging","score":0.503053},{"id":"https://openalex.org/keywords/semantic-segmentation","display_name":"Semantic Segmentation","score":0.501546},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.44248194},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.41255188}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8175497},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6923181},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6460405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.61376345},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.54767764},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.538304},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.47693628},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46095282},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.44248194},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.41255188},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34458667},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.14670181},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.11406857},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.11177391},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-981-99-8558-6_30","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":12,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2464708700","https://openalex.org/W2804047627","https://openalex.org/W2923997689","https://openalex.org/W2996290406","https://openalex.org/W3015788359","https://openalex.org/W3112701542","https://openalex.org/W4212875960","https://openalex.org/W4214546759","https://openalex.org/W4287225447","https://openalex.org/W4313413455","https://openalex.org/W4321232185"],"related_works":["https://openalex.org/W4382323155","https://openalex.org/W4321353415","https://openalex.org/W4315697128","https://openalex.org/W4287067436","https://openalex.org/W4280599700","https://openalex.org/W3205506801","https://openalex.org/W3183570023","https://openalex.org/W2971502891","https://openalex.org/W2745001401","https://openalex.org/W2378211422"],"abstract_inverted_index":{"Due":[0],"to":[1,23,34,100,170],"the":[2,42,47,136,144,151,171,177],"remarkable":[3],"performance":[4,103],"of":[5,46,59,140,161],"Transformers":[6],"in":[7,26,94,123,176],"2D":[8],"medical":[9,19,70],"image":[10,71],"segmentation,":[11],"recent":[12],"studies":[13],"have":[14],"incorporated":[15],"them":[16,33],"into":[17],"3D":[18,69,95],"segmentation":[20,72,102],"tasks.":[21],"Compared":[22],"convolution":[24],"operations":[25],"CNNs,":[27],"Transformer-based":[28],"models":[29],"possess":[30],"self-attention,":[31],"allowing":[32],"capture":[35],"long-range":[36],"dependencies":[37],"among":[38],"pixels.":[39],"To":[40],"address":[41],"high":[43],"computational":[44],"cost":[45],"Transformer":[48,80],"architecture":[49,67],"when":[50],"dealing":[51],"with":[52],"volumetric":[53],"images":[54],"containing":[55],"a":[56,157],"large":[57],"number":[58],"slices,":[60],"we":[61,133],"propose":[62],"an":[63],"efficient":[64],"hybrid":[65],"CNN-Transformer":[66],"for":[68],"named":[73],"PAT-Unet.":[74],"Firstly,":[75],"our":[76,113,141,154],"proposed":[77],"Paired":[78],"Attention":[79],"(PAT)":[81],"blocks":[82],"effectively":[83],"reduce":[84],"spatial":[85,92,130],"dimensions":[86],"while":[87],"proficiently":[88],"learning":[89,128],"channel":[90],"and":[91,108,138,146,165],"information":[93],"feature":[96],"maps.":[97],"This":[98],"leads":[99],"improved":[101],"by":[104,127,167],"reducing":[105,163],"parameter":[106],"count":[107],"accelerating":[109],"computation":[110],"speed.":[111],"Secondly,":[112],"Deformable":[114],"Enhanced":[115],"Skip":[116],"Connection":[117],"(DESC)":[118],"module":[119],"captures":[120],"detailed":[121],"features":[122],"irregular":[124],"lesion":[125],"areas":[126],"volume":[129],"offsets.":[131],"Finally,":[132],"experimentally":[134],"validate":[135],"effectiveness":[137],"efficiency":[139],"model":[142,155],"on":[143],"Synapse":[145,152],"ACDC":[147],"benchmark":[148],"datasets.":[149],"On":[150],"dataset,":[153],"achieves":[156],"Dice":[158],"similarity":[159],"score":[160],"87.17%,":[162],"parameters":[164],"FLOPs":[166],"67%":[168],"compared":[169],"best":[172],"existing":[173],"methods":[174],"reported":[175],"literature.":[178]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4390191237","counts_by_year":[],"updated_date":"2024-10-29T03:50:06.343132","created_date":"2023-12-26"}