{"id":"https://openalex.org/W7167228969","doi":"https://doi.org/10.48550/arxiv.2607.01654","title":"Plug-and-Play Volumetric Reconstruction for Compressive Sensing Light-Sheet Microscopy","display_name":"Plug-and-Play Volumetric Reconstruction for Compressive Sensing Light-Sheet Microscopy","publication_year":2026,"publication_date":"2026-07-02","ids":{"openalex":"https://openalex.org/W7167228969","doi":"https://doi.org/10.48550/arxiv.2607.01654"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.01654","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.01654","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.01654","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139988097","display_name":"Jianqing Jia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia, Jianqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139985947","display_name":"Yi Gong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gong, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139993892","display_name":"Xinyuan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xinyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134548269","display_name":"Jichen Chai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chai, Jichen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049726719","display_name":"Yan Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Yichen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5062067602","display_name":"Yifei Lou","orcid":"https://orcid.org/0000-0003-1973-5704"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lou, Yifei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.4269999861717224,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.4269999861717224,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10540","display_name":"Advanced Fluorescence Microscopy Techniques","score":0.28049999475479126,"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/T12923","display_name":"Digital Image Processing Techniques","score":0.07329999655485153,"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/compressed-sensing","display_name":"Compressed sensing","score":0.8159999847412109},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5846999883651733},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5342000126838684},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.42989999055862427},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.42289999127388},{"id":"https://openalex.org/keywords/reconstruction-algorithm","display_name":"Reconstruction algorithm","score":0.40779998898506165},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.38440001010894775},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3797999918460846},{"id":"https://openalex.org/keywords/multiplexing","display_name":"Multiplexing","score":0.36469998955726624}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.8159999847412109},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5846999883651733},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5665000081062317},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5342000126838684},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48510000109672546},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.42989999055862427},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.42289999127388},{"id":"https://openalex.org/C2779898584","wikidata":"https://www.wikidata.org/wiki/Q7820109","display_name":"Reconstruction algorithm","level":3,"score":0.40779998898506165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4018000066280365},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38670000433921814},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.38440001010894775},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3797999918460846},{"id":"https://openalex.org/C19275194","wikidata":"https://www.wikidata.org/wiki/Q222903","display_name":"Multiplexing","level":2,"score":0.36469998955726624},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.3411000072956085},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.33239999413490295},{"id":"https://openalex.org/C20885615","wikidata":"https://www.wikidata.org/wiki/Q825595","display_name":"Surface reconstruction","level":3,"score":0.32690000534057617},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.31619998812675476},{"id":"https://openalex.org/C147080431","wikidata":"https://www.wikidata.org/wiki/Q1074953","display_name":"Microscopy","level":2,"score":0.30730000138282776},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.29809999465942383},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2976999878883362},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.28279998898506165},{"id":"https://openalex.org/C82233179","wikidata":"https://www.wikidata.org/wiki/Q2054500","display_name":"Partial volume","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.01654","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.01654","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.01654","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.01654","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"investigate":[1],"volumetric":[2,12,69],"reconstruction":[3,48],"for":[4,79,95],"compressive":[5],"sensing":[6],"light-sheet":[7],"microscopy":[8],"(CS-LSM),":[9],"where":[10],"fast":[11],"imaging":[13],"is":[14],"achieved":[15],"by":[16],"encoding":[17],"multiple":[18],"axial":[19],"planes":[20],"into":[21,46,140],"each":[22],"camera":[23],"exposure.":[24],"To":[25],"recover":[26],"the":[27,47,80,85,96,100,114,126,141,149,153],"underlying":[28],"volume":[29],"from":[30,133],"highly":[31],"multiplexed":[32],"measurements,":[33,135],"we":[34,55,74,109],"propose":[35],"a":[36,52,76,92,104],"plug-and-play":[37],"(PnP)":[38],"framework":[39,128,151],"that":[40,61,125],"flexibly":[41],"incorporates":[42],"any":[43],"user-specified":[44],"denoiser":[45],"process.":[49],"Building":[50],"on":[51,118],"slice-based":[53,86],"formulation,":[54],"further":[56],"introduce":[57],"an":[58],"axial-coupled":[59,88,101],"model":[60],"exploits":[62],"correlations":[63],"between":[64],"adjacent":[65],"slices":[66],"to":[67],"improve":[68],"continuity.":[70],"For":[71],"efficient":[72],"computation,":[73],"derive":[75],"Woodbury-based":[77],"update":[78],"data-consistency":[81],"step":[82,98],"in":[83,99],"both":[84],"and":[87,90,120,136],"formulations,":[89],"employ":[91],"Gauss-Seidel":[93],"sweep":[94],"denoising":[97],"model.":[102],"Under":[103],"weakly":[105],"convex":[106],"regularization":[107],"assumption,":[108],"establish":[110],"subsequential":[111],"convergence":[112],"of":[113,144],"proposed":[115,127],"algorithm.":[116],"Experiments":[117],"synthetic":[119],"real":[121],"zebrafish-heart":[122],"data":[123],"demonstrate":[124],"successfully":[129],"recovers":[130],"cellular":[131],"structures":[132],"compressed":[134],"provide":[137],"practical":[138],"insights":[139],"comparative":[142],"performance":[143],"commonly":[145],"used":[146],"denoisers":[147],"within":[148],"PnP":[150],"under":[152],"CS-LSM":[154],"setup.":[155]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-04T00:00:00"}
