{"id":"https://openalex.org/W4221081331","doi":"https://doi.org/10.1117/12.2605538","title":"Efficient network with ghost tied block for heart segmentation","display_name":"Efficient network with ghost tied block for heart segmentation","publication_year":2022,"publication_date":"2022-03-31","ids":{"openalex":"https://openalex.org/W4221081331","doi":"https://doi.org/10.1117/12.2605538"},"language":"en","primary_location":{"id":"doi:10.1117/12.2605538","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2605538","pdf_url":null,"source":{"id":"https://openalex.org/S4363607561","display_name":"Medical Imaging 2022: Image Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2022: Image Processing","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/A5053191073","display_name":"Yuhao Guo","orcid":"https://orcid.org/0000-0002-5364-3339"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]},{"id":"https://openalex.org/I4210099079","display_name":"Institute of Intelligent Machines","ror":"https://ror.org/00w0qep84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I2802624667","https://openalex.org/I4210099079"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuhao Guo","raw_affiliation_strings":["Anhui Univ. (China)","Institute of Intelligent Machines (China)"],"affiliations":[{"raw_affiliation_string":"Anhui Univ. (China)","institution_ids":["https://openalex.org/I143868143"]},{"raw_affiliation_string":"Institute of Intelligent Machines (China)","institution_ids":["https://openalex.org/I4210099079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100636117","display_name":"Bin Cai","orcid":"https://orcid.org/0009-0001-0234-4611"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210099079","display_name":"Institute of Intelligent Machines","ror":"https://ror.org/00w0qep84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I2802624667","https://openalex.org/I4210099079"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Cai","raw_affiliation_strings":["Institute of Intelligent Machines (China)","Univ. of Science and Technology of China (China)"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Machines (China)","institution_ids":["https://openalex.org/I4210099079"]},{"raw_affiliation_string":"Univ. of Science and Technology of China (China)","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088454284","display_name":"Pengpeng Liang","orcid":"https://orcid.org/0000-0001-5124-5727"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengpeng Liang","raw_affiliation_strings":["Zhengzhou Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Zhengzhou Univ. (China)","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100648002","display_name":"Kaifeng Wang","orcid":"https://orcid.org/0000-0002-8083-2258"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210124809","display_name":"Peking University People's Hospital","ror":"https://ror.org/035adwg89","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210124809"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaifeng Wang","raw_affiliation_strings":["Peking Univ. People's Hospital (China)"],"affiliations":[{"raw_affiliation_string":"Peking Univ. People's Hospital (China)","institution_ids":["https://openalex.org/I4210124809","https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101727179","display_name":"Zhiyong Sun","orcid":"https://orcid.org/0000-0001-9510-4897"},"institutions":[{"id":"https://openalex.org/I4210099079","display_name":"Institute of Intelligent Machines","ror":"https://ror.org/00w0qep84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I2802624667","https://openalex.org/I4210099079"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Sun","raw_affiliation_strings":["Institute of Intelligent Machines (China)"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Machines (China)","institution_ids":["https://openalex.org/I4210099079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102676441","display_name":"Chi Xiong","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210099079","display_name":"Institute of Intelligent Machines","ror":"https://ror.org/00w0qep84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I2802624667","https://openalex.org/I4210099079"]},{"id":"https://openalex.org/I4210134906","display_name":"First Affiliated Hospital of Henan University of Science and Technology","ror":"https://ror.org/035zbbv42","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210134906"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chi Xiong","raw_affiliation_strings":["Institute of Intelligent Machines (China)","The First Affiliated Hospital of Univ. of Science and Technology of China (China)","Univ. of Science and Technology of China (China)"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Machines (China)","institution_ids":["https://openalex.org/I4210099079"]},{"raw_affiliation_string":"The First Affiliated Hospital of Univ. of Science and Technology of China (China)","institution_ids":["https://openalex.org/I4210134906","https://openalex.org/I126520041"]},{"raw_affiliation_string":"Univ. of Science and Technology of China (China)","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002668522","display_name":"Bo Song","orcid":"https://orcid.org/0000-0002-1850-7841"},"institutions":[{"id":"https://openalex.org/I4210099079","display_name":"Institute of Intelligent Machines","ror":"https://ror.org/00w0qep84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I2802624667","https://openalex.org/I4210099079"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Song","raw_affiliation_strings":["Institute of Intelligent Machines (China)"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Machines (China)","institution_ids":["https://openalex.org/I4210099079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073823550","display_name":"Chaoshi Niu","orcid":"https://orcid.org/0000-0002-9079-681X"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210134906","display_name":"First Affiliated Hospital of Henan University of Science and Technology","ror":"https://ror.org/035zbbv42","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210134906"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaoshi Niu","raw_affiliation_strings":["The First Affiliated Hospital of Univ. of Science and Technology of China (China)"],"affiliations":[{"raw_affiliation_string":"The First Affiliated Hospital of Univ. of Science and Technology of China (China)","institution_ids":["https://openalex.org/I4210134906","https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059137735","display_name":"Erkang Cheng","orcid":"https://orcid.org/0000-0001-7941-6911"},"institutions":[{"id":"https://openalex.org/I4210099079","display_name":"Institute of Intelligent Machines","ror":"https://ror.org/00w0qep84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I2802624667","https://openalex.org/I4210099079"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Erkang Cheng","raw_affiliation_strings":["Institute of Intelligent Machines (China)"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Machines (China)","institution_ids":["https://openalex.org/I4210099079"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5053191073"],"corresponding_institution_ids":["https://openalex.org/I143868143","https://openalex.org/I4210099079"],"apc_list":null,"apc_paid":null,"fwci":0.0597,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.22228531,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"8","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":0.9988999962806702,"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":0.9988999962806702,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9939000010490417,"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"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.98580002784729,"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/convolution","display_name":"Convolution (computer science)","score":0.8317384719848633},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7428011894226074},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.7296364307403564},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7180423140525818},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6659852862358093},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5677599310874939},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5616076588630676},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.5115126371383667},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47819069027900696},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4317007064819336},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.42312419414520264},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3869611620903015},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33540254831314087},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2232389748096466},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1254291832447052},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.1082821786403656},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09429478645324707},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.0619659423828125}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.8317384719848633},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7428011894226074},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.7296364307403564},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7180423140525818},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6659852862358093},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5677599310874939},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5616076588630676},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.5115126371383667},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47819069027900696},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4317007064819336},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.42312419414520264},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3869611620903015},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33540254831314087},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2232389748096466},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1254291832447052},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.1082821786403656},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09429478645324707},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0619659423828125},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2605538","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2605538","pdf_url":null,"source":{"id":"https://openalex.org/S4363607561","display_name":"Medical Imaging 2022: Image Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2022: Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2163605009","https://openalex.org/W2798122705","https://openalex.org/W2884561390","https://openalex.org/W2965270294","https://openalex.org/W2966333895","https://openalex.org/W3028038068","https://openalex.org/W3035414587","https://openalex.org/W3088934216","https://openalex.org/W3165136712","https://openalex.org/W4297775537","https://openalex.org/W6639824700","https://openalex.org/W6684191040","https://openalex.org/W6737664043","https://openalex.org/W6742348326","https://openalex.org/W6742939860","https://openalex.org/W6748498557","https://openalex.org/W6748743940","https://openalex.org/W6749401086","https://openalex.org/W6749651325","https://openalex.org/W6749708034","https://openalex.org/W6749718306","https://openalex.org/W6749923946","https://openalex.org/W6750043147","https://openalex.org/W6750558302","https://openalex.org/W6755182100","https://openalex.org/W6767623350","https://openalex.org/W6770473083","https://openalex.org/W6777431904","https://openalex.org/W6795809246"],"related_works":["https://openalex.org/W4315697128","https://openalex.org/W4382323155","https://openalex.org/W3205506801","https://openalex.org/W2971502891","https://openalex.org/W3005814217","https://openalex.org/W2982536526","https://openalex.org/W2995343971","https://openalex.org/W2964954556","https://openalex.org/W2992221004","https://openalex.org/W3019910406"],"abstract_inverted_index":{"Heart":[0],"segmentation":[1,200],"plays":[2],"an":[3,77],"important":[4],"role":[5],"in":[6,43,171,176],"accurate":[7],"diagnosis":[8],"and":[9,115,155,174,208],"treatment":[10],"of":[11,52,61,101],"cardiovascular":[12],"disease.":[13],"More":[14],"recently,":[15],"deep":[16],"convolutional":[17],"neural":[18],"networks":[19],"(CNN)":[20],"are":[21],"predominant":[22],"to":[23,69,75,118,134,150,181],"many":[24],"medical":[25],"image":[26],"analysis":[27],"applications":[28],"including":[29],"3D":[30,35,53,92,185],"heart":[31,199],"segmentation.":[32,45],"For":[33],"example,":[34],"UNet":[36],"with":[37,123,130,147,190,204],"U-shape":[38],"encoder-decoder":[39],"architecture":[40],"performs":[41],"well":[42],"volumetric":[44],"However,":[46],"standard":[47,144],"convolution,":[48],"the":[49,131,177,196],"building":[50],"block":[51],"CNN":[54],"network":[55],"usually":[56],"contains":[57],"a":[58,71,89,98],"large":[59],"number":[60,100],"parameters.":[62],"In":[63],"this":[64,109],"paper,":[65],"our":[66,188],"objective":[67],"is":[68,116,169],"investigate":[70],"light":[72],"convolution":[73,102,145,166],"module":[74,133,142],"build":[76],"efficient":[78],"network.":[79],"Inspired":[80],"by":[81,160],"2D":[82],"Tied":[83,90,137],"Block":[84,91,138],"Convolution":[85,93],"(TBC),":[86],"we":[87,127],"introduce":[88],"(TBC-3D)":[94],"operator":[95],"which":[96],"reuses":[97],"small":[99],"filters":[103,149],"across":[104],"each":[105],"channel":[106],"group.":[107],"To":[108],"end,":[110],"TBC-3D":[111,129,168],"requires":[112],"fewer":[113,210],"parameters":[114,207],"able":[117],"obtain":[119,151],"more":[120,158],"feature":[121,153],"maps":[122],"high":[124],"performance.":[125],"Furthermore,":[126],"combine":[128],"Ghost-3D":[132,178],"construct":[135],"Ghost":[136,141],"(GTB).":[139],"Specifically,":[140],"employs":[143],"(OP1)":[146],"few":[148],"intrinsic":[152],"maps,":[154],"then":[156],"generates":[157],"features":[159],"cheap":[161],"linear":[162],"operation":[163],"like":[164],"depth-wise":[165],"(OP2).":[167],"applied":[170],"both":[172],"OP1":[173],"OP2":[175],"module.":[179],"Compared":[180],"state-of-the-art":[182],"solutions":[183],"using":[184],"UNet-like":[186],"architecture,":[187],"model":[189],"GTB":[191],"achieves":[192],"competitive":[193],"performance":[194],"on":[195],"MM-WHS":[197],"whole":[198],"Challenge":[201],"2017":[202],"datasets":[203],"2.31x":[205],"less":[206],"1.93x":[209],"FLOPs.":[211]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}