{"id":"https://openalex.org/W3005413869","doi":"https://doi.org/10.1109/tmi.2020.2972059","title":"Recalibrating 3D ConvNets With Project & Excite","display_name":"Recalibrating 3D ConvNets With Project & Excite","publication_year":2020,"publication_date":"2020-02-06","ids":{"openalex":"https://openalex.org/W3005413869","doi":"https://doi.org/10.1109/tmi.2020.2972059","mag":"3005413869","pmid":"https://pubmed.ncbi.nlm.nih.gov/32031934"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2020.2972059","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2020.2972059","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2002.10994","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Anne-Marie Rickmann","orcid":"https://orcid.org/0000-0002-7432-0782"},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Anne-Marie Rickmann","raw_affiliation_strings":["Laboratory for Artificial Intelligence in Medical Imaging (AI-Med), University Hospital, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, Munich, Germany"],"raw_orcid":"https://orcid.org/0000-0002-7432-0782","affiliations":[{"raw_affiliation_string":"Laboratory for Artificial Intelligence in Medical Imaging (AI-Med), University Hospital, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Abhijit Guha Roy","orcid":"https://orcid.org/0000-0001-7221-468X"},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Abhijit Guha Roy","raw_affiliation_strings":["Laboratory for Artificial Intelligence in Medical Imaging (AI-Med), University Hospital, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, Munich, Germany"],"raw_orcid":"https://orcid.org/0000-0001-7221-468X","affiliations":[{"raw_affiliation_string":"Laboratory for Artificial Intelligence in Medical Imaging (AI-Med), University Hospital, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ignacio Sarasua","orcid":null},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ignacio Sarasua","raw_affiliation_strings":["Laboratory for Artificial Intelligence in Medical Imaging (AI-Med), University Hospital, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory for Artificial Intelligence in Medical Imaging (AI-Med), University Hospital, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"last","author":{"id":null,"display_name":"Christian Wachinger","orcid":null},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christian Wachinger","raw_affiliation_strings":["Laboratory for Artificial Intelligence in Medical Imaging (AI-Med), University Hospital, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory for Artificial Intelligence in Medical Imaging (AI-Med), University Hospital, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I8204097"],"apc_list":null,"apc_paid":null,"fwci":1.9167,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.88069277,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"39","issue":"7","first_page":"2461","last_page":"2471"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.7415000200271606,"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":0.7415000200271606,"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":0.04390000179409981,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.04050000011920929,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/boosting","display_name":"Boosting (machine learning)","score":0.7982000112533569},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.7387999892234802},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7264999747276306},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6708999872207642},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5412999987602234},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5309000015258789},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49950000643730164},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49000000953674316}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7982000112533569},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7645999789237976},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.7387999892234802},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.73089998960495},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7264999747276306},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6708999872207642},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5412999987602234},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5309000015258789},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5202000141143799},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49950000643730164},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49000000953674316},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.47920000553131104},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42250001430511475},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4072999954223633},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.39419999718666077},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3174999952316284},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.29179999232292175},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.26660001277923584},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tmi.2020.2972059","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2020.2972059","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:32031934","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32031934","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on medical imaging","raw_type":null},{"id":"pmh:oai:arXiv.org:2002.10994","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2002.10994","pdf_url":"https://arxiv.org/pdf/2002.10994","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2002.10994","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2002.10994","pdf_url":"https://arxiv.org/pdf/2002.10994","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W1969094805","https://openalex.org/W2078524519","https://openalex.org/W2124260444","https://openalex.org/W2292862470","https://openalex.org/W2301358467","https://openalex.org/W2412453619","https://openalex.org/W2412782625","https://openalex.org/W2464708700","https://openalex.org/W2572730214","https://openalex.org/W2589647984","https://openalex.org/W2608353599","https://openalex.org/W2752782242","https://openalex.org/W2888493720","https://openalex.org/W2900237898","https://openalex.org/W2901434856","https://openalex.org/W2946523827","https://openalex.org/W2962914239","https://openalex.org/W2963668330","https://openalex.org/W2963730812","https://openalex.org/W2963881378","https://openalex.org/W2980844262","https://openalex.org/W6639824700","https://openalex.org/W6746012787","https://openalex.org/W6753412334","https://openalex.org/W6754239853"],"related_works":[],"abstract_inverted_index":{"Fully":[0],"Convolutional":[1],"Neural":[2],"Networks":[3],"(F-CNNs)":[4],"achieve":[5],"state-of-the-art":[6],"performance":[7,39,176],"for":[8,87,102],"segmentation":[9,38,153,159],"tasks":[10],"in":[11,140,180],"computer":[12],"vision":[13],"and":[14,22,35,81,157,183],"medical":[15,61],"imaging.":[16],"Recently,":[17],"computational":[18],"blocks":[19,53],"termed":[20],"squeeze":[21],"excitation":[23,142],"(SE)":[24],"have":[25],"been":[26],"introduced":[27],"to":[28,79,107,131,178],"recalibrate":[29],"F-CNN":[30],"feature":[31,121],"maps":[32,122],"both":[33],"channel-":[34],"spatial-wise,":[36],"boosting":[37,175],"while":[40,191],"only":[41,192],"minimally":[42],"increasing":[43,194],"the":[44,49,128,141,146,195],"model":[45,196],"complexity.":[46,197],"So":[47],"far,":[48],"development":[50],"of":[51,90,127,154,160,187],"SE":[52],"has":[54],"focused":[55],"on":[56,148,203],"2D":[57,76],"architectures.":[58],"For":[59],"volumetric":[60],"images,":[62],"however,":[63],"3D":[64,80,103,173,185],"F-CNNs":[65],"are":[66],"a":[67,83],"natural":[68],"choice.":[69],"In":[70,105],"this":[71],"article,":[72],"we":[73],"extend":[74],"existing":[75,108],"recalibration":[77,189],"methods":[78],"propose":[82],"generic":[84],"compress-process-recalibrate":[85],"pipeline":[86],"easy":[88],"comparison":[89],"such":[91],"blocks.":[92],"We":[93,144,163],"further":[94],"introduce":[95],"Project":[96,110],"&":[97,111],"Excite":[98,112],"(PE)":[99],"modules,":[100,109],"customized":[101],"networks.":[104],"contrast":[106],"does":[113],"not":[114],"perform":[115],"global":[116],"average":[117],"pooling":[118],"but":[119],"compresses":[120],"along":[123],"different":[124],"spatial":[125,134],"dimensions":[126],"tensor":[129],"separately":[130],"retain":[132],"more":[133],"information":[135],"that":[136,165],"is":[137,200],"subsequently":[138],"used":[139],"step.":[143],"evaluate":[145],"modules":[147,167],"two":[149],"challenging":[150],"tasks,":[151],"whole-brain":[152],"MRI":[155],"scans":[156],"whole-body":[158],"CT":[161],"scans.":[162],"demonstrate":[164],"PE":[166],"can":[168],"be":[169],"easily":[170],"integrated":[171],"into":[172],"F-CNNs,":[174],"up":[177],"0.3":[179],"Dice":[181],"Score":[182],"outperforming":[184],"extensions":[186],"other":[188],"blocks,":[190],"marginally":[193],"Our":[198],"code":[199],"publicly":[201],"available":[202],"https://github.com/ai-med/squeezeandexcitation.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2020-02-14T00:00:00"}