{"id":"https://openalex.org/W2983655804","doi":"https://doi.org/10.23919/eusipco.2019.8903041","title":"Fast Alignment of Limited Angle Tomograms by projected Cross Correlation","display_name":"Fast Alignment of Limited Angle Tomograms by projected Cross Correlation","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2983655804","doi":"https://doi.org/10.23919/eusipco.2019.8903041","mag":"2983655804"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2019.8903041","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2019.8903041","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th European Signal Processing Conference (EUSIPCO)","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/A5025888661","display_name":"Ricardo M. S\u00e1nchez","orcid":"https://orcid.org/0000-0002-2854-0119"},"institutions":[{"id":"https://openalex.org/I4210124035","display_name":"Max Planck Institute of Biophysics","ror":"https://ror.org/02panr271","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210124035"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Ricardo M. Sanchez","raw_affiliation_strings":["Max Planck Institute for Biophysics, Frankfurt am Main, Germany"],"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Biophysics, Frankfurt am Main, Germany","institution_ids":["https://openalex.org/I4210124035"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048393027","display_name":"Rudolf Mester","orcid":"https://orcid.org/0000-0002-6932-0606"},"institutions":[{"id":"https://openalex.org/I114090438","display_name":"Goethe University Frankfurt","ror":"https://ror.org/04cvxnb49","country_code":"DE","type":"education","lineage":["https://openalex.org/I114090438"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Rudolf Mester","raw_affiliation_strings":["visual Sensorics & Inf. Proc. Lab, Goethe University, Germany"],"affiliations":[{"raw_affiliation_string":"visual Sensorics & Inf. Proc. Lab, Goethe University, Germany","institution_ids":["https://openalex.org/I114090438"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039296218","display_name":"Mikhail Kudryashev","orcid":"https://orcid.org/0000-0003-3550-6274"},"institutions":[{"id":"https://openalex.org/I4210124035","display_name":"Max Planck Institute of Biophysics","ror":"https://ror.org/02panr271","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210124035"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mikhail Kudryashev","raw_affiliation_strings":["Max Planck Institute for Biophysics, Frankfurt am Main, Germany"],"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Biophysics, Frankfurt am Main, Germany","institution_ids":["https://openalex.org/I4210124035"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025888661"],"corresponding_institution_ids":["https://openalex.org/I4210124035"],"apc_list":null,"apc_paid":null,"fwci":0.1756,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.76035782,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10857","display_name":"Advanced Electron Microscopy Techniques and Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1315","display_name":"Structural Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10857","display_name":"Advanced Electron Microscopy Techniques and Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1315","display_name":"Structural Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11786","display_name":"Geomagnetism and Paleomagnetism Studies","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12039","display_name":"Electron and X-Ray Spectroscopy Techniques","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/2508","display_name":"Surfaces, Coatings and Films"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cross-correlation","display_name":"Cross-correlation","score":0.6638036966323853},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5708054304122925},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5377047657966614},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4947201907634735},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.4891210198402405},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4580075442790985},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4478045701980591},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.42924174666404724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42804989218711853},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.42229196429252625},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3530275523662567},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2766501009464264},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.1514405608177185},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.12205767631530762},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12205660343170166},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09840857982635498},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.06999656558036804}],"concepts":[{"id":"https://openalex.org/C163018871","wikidata":"https://www.wikidata.org/wiki/Q1302587","display_name":"Cross-correlation","level":2,"score":0.6638036966323853},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5708054304122925},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5377047657966614},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4947201907634735},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.4891210198402405},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4580075442790985},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4478045701980591},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.42924174666404724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42804989218711853},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.42229196429252625},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3530275523662567},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2766501009464264},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.1514405608177185},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12205767631530762},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12205660343170166},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09840857982635498},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.06999656558036804},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.23919/eusipco.2019.8903041","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2019.8903041","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},{"id":"pmh:oai:edoc.mdc-berlin.de:20528","is_oa":false,"landing_page_url":"http://edoc.mdc-berlin.de/20528/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400224","display_name":"MDC Repository (Max-Delbrueck-Center for Molecular Medicine)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1594672787","https://openalex.org/W1964979024","https://openalex.org/W1996763106","https://openalex.org/W2040102384","https://openalex.org/W2044999421","https://openalex.org/W2051555473","https://openalex.org/W2066352158","https://openalex.org/W2115251427","https://openalex.org/W2587625522","https://openalex.org/W2618154850","https://openalex.org/W2618224103","https://openalex.org/W2769523708","https://openalex.org/W2945513101","https://openalex.org/W2963921324","https://openalex.org/W6737984792"],"related_works":["https://openalex.org/W1982833409","https://openalex.org/W2351879100","https://openalex.org/W2127233063","https://openalex.org/W1995086486","https://openalex.org/W2224601872","https://openalex.org/W2477816036","https://openalex.org/W1491349473","https://openalex.org/W2036133287","https://openalex.org/W2905963123","https://openalex.org/W2023655541"],"abstract_inverted_index":{"Volume":[0],"alignment":[1,196],"is":[2,161,178,185],"a":[3,21,35,53,79,84,92,97,106,128],"computationally":[4],"intensive":[5],"task.":[6],"In":[7],"Subtomogram":[8,150],"Averaging":[9,141,151],"(StA)":[10],"from":[11],"electron":[12],"cryotomograms":[13],"(CryoET),":[14],"thousands":[15],"of":[16,29,38,133,195,197],"subtomograms":[17,49,198],"are":[18,50,72],"aligned":[19,51],"to":[20,52,87,104,116,147],"reference,":[22,99],"which":[23],"may":[24],"take":[25],"hours":[26],"until":[27],"days":[28],"computational":[30,122],"time.":[31],"CryoET":[32],"datasets":[33],"contain":[34],"limited":[36,66,93],"number":[37],"noisy":[39,48],"projections,":[40],"with":[41,65,120,127],"very":[42],"low":[43],"signal-to-until":[44],"ratio":[45],"(SNR).":[46],"The":[47],"reference":[54,166],"using":[55],"cross-correlation,":[56],"an":[57,145],"operation":[58],"that":[59,159],"can":[60],"be":[61],"optimized":[62],"when":[63],"working":[64],"angle":[67,94],"tomograms":[68],"(LAT),":[69],"as":[70,124,144],"they":[71],"sparse":[73],"in":[74,192],"Fourier":[75],"space.":[76],"We":[77],"propose":[78,138],"projected":[80],"cross-correlation":[81,90,119],"(pCC)":[82],"algorithm,":[83],"faster":[85,163],"approach":[86],"computing":[88],"the":[89,114,118,139,148,165,176],"between":[91],"(sub)-tomogram":[95],"and":[96,100,174,182],"given":[98],"we":[101,137],"use":[102],"pCC":[103,112],"design":[105],"new":[107],"procedure":[108],"for":[109,169,183],"volume":[110],"alignment.":[111],"employs":[113],"projections":[115,131,171],"calculate":[117],"lower":[121],"complexity,":[123],"it":[125],"works":[126],"set":[129],"2D":[130],"instead":[132],"volumes.":[134],"With":[135],"this,":[136],"Substacks":[140],"(SsA)":[142],"method":[143],"alternative":[146],"conventional":[149],"(StA).":[152],"Our":[153],"results":[154,191],"on":[155],"test":[156],"data":[157],"shows":[158],"SsA":[160,177,190],"considerably":[162],"than":[164],"StA":[167],"implementation:":[168],"41":[170],"(k=":[172],"41)":[173],"N=200,":[175],"35":[179],"times":[180,187],"faster,":[181],"N=320,":[184],"150":[186],"faster.":[188],"Furthermore,":[189],"higher":[193],"precision":[194],"at":[199],"different":[200],"noise":[201],"levels.":[202]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}