{"id":"https://openalex.org/W7140271948","doi":"https://doi.org/10.48550/arxiv.2603.22311","title":"Ca2+ transient detection and segmentation with the Astronomically motivated algorithm for Background Estimation And Transient Segmentation (Astro-BEATS)","display_name":"Ca2+ transient detection and segmentation with the Astronomically motivated algorithm for Background Estimation And Transient Segmentation (Astro-BEATS)","publication_year":2026,"publication_date":"2026-03-19","ids":{"openalex":"https://openalex.org/W7140271948","doi":"https://doi.org/10.48550/arxiv.2603.22311"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.22311","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22311","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.22311","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101863813","display_name":"Bi Fan","orcid":"https://orcid.org/0000-0003-2193-6943"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Fan, Bolin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040560517","display_name":"Anthony Bilodeau","orcid":"https://orcid.org/0000-0002-7041-6402"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bilodeau, Anthony","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114724666","display_name":"Frederic Beaupr\u00e9","orcid":"https://orcid.org/0009-0000-4412-5153"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Beaupre, Frederic","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009549493","display_name":"Theresa Wiesner","orcid":"https://orcid.org/0000-0001-5620-2945"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wiesner, Theresa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045218915","display_name":"Christian Gagn\u00e9","orcid":"https://orcid.org/0000-0003-3697-4184"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gagne, Christian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125418904","display_name":"Flavie Lavoie-Cardinal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lavoie-Cardinal, Flavie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5003942693","display_name":"Ren\u00e9e Hlo\u017eek","orcid":"https://orcid.org/0000-0002-0965-7864"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hlozek, Renee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101863813"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.20819999277591705,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.20819999277591705,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10077","display_name":"Neuroscience and Neuropharmacology Research","score":0.17170000076293945,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.14219999313354492,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/transient","display_name":"Transient (computer programming)","score":0.7771999835968018},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7174000144004822},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5130000114440918},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4844000041484833},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.44369998574256897},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3598000109195709}],"concepts":[{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.7771999835968018},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7174000144004822},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6309999823570251},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6126999855041504},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5130000114440918},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5037000179290771},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4844000041484833},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.44369998574256897},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4025999903678894},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3598000109195709},{"id":"https://openalex.org/C100675267","wikidata":"https://www.wikidata.org/wiki/Q1371624","display_name":"Background noise","level":2,"score":0.32179999351501465},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C85761212","wikidata":"https://www.wikidata.org/wiki/Q1974593","display_name":"Transient response","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C2989121073","wikidata":"https://www.wikidata.org/wiki/Q1309019","display_name":"Transient analysis","level":3,"score":0.2741999924182892}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.22311","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22311","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.22311","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22311","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Fluorescence-based":[0],"Ca$^{2+}$-imaging":[1,110,145],"is":[2],"a":[3,38,60,133],"powerful":[4],"tool":[5],"for":[6,41,77,109,117,138,164,168],"studying":[7],"localized":[8],"neuronal":[9],"activity,":[10],"including":[11],"miniature":[12,78,91],"Synaptic":[13,79,92],"Calcium":[14,80,93],"Transients,":[15],"providing":[16],"real-time":[17],"insights":[18],"into":[19],"synaptic":[20,43,118,140],"activity.":[21],"These":[22],"transients":[23,50],"induce":[24],"only":[25],"subtle":[26],"changes":[27],"in":[28,73,83,105,144],"the":[29],"fluorescence":[30,84],"signal,":[31],"often":[32],"barely":[33],"above":[34],"baseline,":[35],"which":[36],"poses":[37],"significant":[39],"challenge":[40],"automated":[42],"transient":[44,75,120,142],"detection":[45,76,82,121,143],"and":[46,101,107,122,151],"segmentation.":[47,123],"Detecting":[48],"astronomical":[49,74],"similarly":[51],"requires":[52],"efficient":[53],"algorithms":[54],"that":[55,97],"will":[56],"remain":[57],"robust":[58],"over":[59],"large":[61],"field":[62],"of":[63,149],"view":[64],"with":[65],"varying":[66],"noise":[67],"properties.":[68],"We":[69,86],"leverage":[70],"techniques":[71,103],"used":[72,104,130],"Transient":[81,94],"microscopy.":[85],"present":[87],"Astro-BEATS,":[88],"an":[89],"automatic":[90],"segmentation":[95,126],"algorithm":[96,137],"incorporates":[98],"image":[99],"estimation":[100],"source-finding":[102],"astronomy":[106],"designed":[108],"videos.":[111],"Astro-BEATS":[112,150],"outperforms":[113],"current":[114],"threshold-based":[115],"approaches":[116],"Ca$^{2+}$":[119,141],"The":[124,147],"produced":[125],"masks":[127],"can":[128],"be":[129],"to":[131,154],"train":[132],"supervised":[134],"deep":[135,169],"learning":[136],"improved":[139],"data.":[146],"speed":[148],"its":[152],"applicability":[153],"previously":[155],"unseen":[156],"datasets":[157,167],"without":[158],"re-optimization":[159],"makes":[160],"it":[161],"particularly":[162],"useful":[163],"generating":[165],"training":[166],"learning-based":[170],"approaches.":[171]},"counts_by_year":[],"updated_date":"2026-05-04T08:30:34.212998","created_date":"2026-03-26T00:00:00"}
