{"id":"https://openalex.org/W2920109701","doi":"https://doi.org/10.1109/acssc.2018.8645460","title":"Bayesian filtering for spatial estimation of photo-switching fluorophores imaged in Super-resolution fluorescence microscopy","display_name":"Bayesian filtering for spatial estimation of photo-switching fluorophores imaged in Super-resolution fluorescence microscopy","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2920109701","doi":"https://doi.org/10.1109/acssc.2018.8645460","mag":"2920109701"},"language":"en","primary_location":{"id":"doi:10.1109/acssc.2018.8645460","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2018.8645460","pdf_url":null,"source":{"id":"https://openalex.org/S4363608623","display_name":"2018 52nd Asilomar Conference on Signals, Systems, and Computers","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":"2018 52nd Asilomar Conference on Signals, Systems, and Computers","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/A5064424320","display_name":"Lekha Patel","orcid":"https://orcid.org/0000-0003-3508-0672"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lekha Patel","raw_affiliation_strings":["Department of Mathematics, Imperial College London, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Imperial College London, London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081632927","display_name":"Edward A. K. Cohen","orcid":"https://orcid.org/0000-0002-8594-9623"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Edward A.K. Cohen","raw_affiliation_strings":["Department of Mathematics, Imperial College London, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Imperial College London, London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.60576923,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"21","issue":null,"first_page":"1187","last_page":"1191"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10540","display_name":"Advanced Fluorescence Microscopy Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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/T10540","display_name":"Advanced Fluorescence Microscopy Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.982200026512146,"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/microscopy","display_name":"Microscopy","score":0.5869117975234985},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.5722435712814331},{"id":"https://openalex.org/keywords/fluorescence","display_name":"Fluorescence","score":0.536782443523407},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5212289094924927},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5204396843910217},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.5086110830307007},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5075231790542603},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.49475497007369995},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.45518064498901367},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44779539108276367},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4278806149959564},{"id":"https://openalex.org/keywords/biological-system","display_name":"Biological system","score":0.421744167804718},{"id":"https://openalex.org/keywords/photon","display_name":"Photon","score":0.4138141870498657},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.3856986463069916},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.383939266204834},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.36830630898475647},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3437000513076782},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.31598925590515137},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21214303374290466},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10153338313102722},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.09299030900001526}],"concepts":[{"id":"https://openalex.org/C147080431","wikidata":"https://www.wikidata.org/wiki/Q1074953","display_name":"Microscopy","level":2,"score":0.5869117975234985},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.5722435712814331},{"id":"https://openalex.org/C91881484","wikidata":"https://www.wikidata.org/wiki/Q191807","display_name":"Fluorescence","level":2,"score":0.536782443523407},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5212289094924927},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5204396843910217},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.5086110830307007},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5075231790542603},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.49475497007369995},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.45518064498901367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44779539108276367},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4278806149959564},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.421744167804718},{"id":"https://openalex.org/C159317903","wikidata":"https://www.wikidata.org/wiki/Q3198","display_name":"Photon","level":2,"score":0.4138141870498657},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.3856986463069916},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.383939266204834},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.36830630898475647},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3437000513076782},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.31598925590515137},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21214303374290466},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10153338313102722},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.09299030900001526},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acssc.2018.8645460","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2018.8645460","pdf_url":null,"source":{"id":"https://openalex.org/S4363608623","display_name":"2018 52nd Asilomar Conference on Signals, Systems, and Computers","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":"2018 52nd Asilomar Conference on Signals, Systems, and Computers","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":23,"referenced_works":["https://openalex.org/W34992941","https://openalex.org/W158497669","https://openalex.org/W1519516901","https://openalex.org/W1531532259","https://openalex.org/W1978520421","https://openalex.org/W1985242342","https://openalex.org/W1992858116","https://openalex.org/W2014787937","https://openalex.org/W2054455698","https://openalex.org/W2071625890","https://openalex.org/W2072625186","https://openalex.org/W2077765533","https://openalex.org/W2086470518","https://openalex.org/W2101336703","https://openalex.org/W2105905583","https://openalex.org/W2106316394","https://openalex.org/W2125505095","https://openalex.org/W2157456092","https://openalex.org/W2238582461","https://openalex.org/W2780673665","https://openalex.org/W2980815417","https://openalex.org/W6606411000","https://openalex.org/W6747109530"],"related_works":["https://openalex.org/W2151689585","https://openalex.org/W2380816257","https://openalex.org/W3087071515","https://openalex.org/W4283726152","https://openalex.org/W1525770572","https://openalex.org/W1485888979","https://openalex.org/W3172507773","https://openalex.org/W2806680938","https://openalex.org/W4302285290","https://openalex.org/W4399590296"],"abstract_inverted_index":{"The":[0],"success":[1],"of":[2,12,16,27,57],"many":[3],"Super-resolution":[4],"fluorescence":[5],"microscopy":[6],"methods":[7],"lie":[8],"in":[9],"the":[10,13,80],"exploitation":[11],"inherent":[14],"stochasticity":[15],"a":[17,64,94],"light":[18],"emitting":[19],"molecule's":[20],"photon":[21],"emission":[22],"state,":[23],"allowing":[24],"sparse":[25],"subsets":[26],"molecules":[28],"to":[29,54],"be":[30,88],"spatially":[31],"detected":[32],"with":[33,71],"high":[34],"precision.":[35],"This":[36],"photo-switching":[37],"behavior,":[38],"however,":[39],"induces":[40],"multiple":[41],"localizations":[42],"from":[43],"each":[44],"molecule":[45],"during":[46],"an":[47],"imaging":[48],"experiment,":[49],"which":[50],"therefore":[51],"gives":[52],"rise":[53],"misleading":[55],"representations":[56],"their":[58],"true":[59,68],"spatial":[60],"locations.":[61],"By":[62],"formulating":[63],"state-space":[65],"model":[66],"relating":[67],"molecular":[69],"positions":[70,91],"observation":[72],"sets":[73],"collected":[74],"across":[75],"time,":[76],"we":[77],"show":[78],"that":[79],"full":[81],"Bayes":[82],"filter":[83],"for":[84],"this":[85],"problem":[86],"can":[87],"derived":[89],"and":[90],"recovered":[92],"via":[93],"Markov":[95],"Chain":[96],"Monte":[97],"Carlo":[98],"sampler.":[99]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
