{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T16:20:58Z","timestamp":1771950058699,"version":"3.50.1"},"reference-count":20,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T00:00:00Z","timestamp":1669593600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61931008"],"award-info":[{"award-number":["61931008"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U21B2024"],"award-info":[{"award-number":["U21B2024"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62071415"],"award-info":[{"award-number":["62071415"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62071219"],"award-info":[{"award-number":["62071219"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62088102"],"award-info":[{"award-number":["62088102"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Light-field microscopy (LFM) is a compact solution to high-speed 3D fluorescence imaging. Usually, we need to do 3D deconvolution to the captured raw data. Although there are deep neural network methods that can accelerate the reconstruction process, the model is not universally applicable for all system parameters. Here, we develop AutoDeconJ, a GPU-accelerated ImageJ plugin for 4.4\u00d7 faster and more accurate deconvolution of LFM data. We further propose an image quality metric for the deconvolution process, aiding in automatically determining the optimal number of iterations with higher reconstruction accuracy and fewer artifacts.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Our proposed method outperforms state-of-the-art light-field deconvolution methods in reconstruction time and optimal iteration numbers prediction capability. It shows better universality of different light-field point spread function (PSF) parameters than the deep learning method. The fast, accurate and general reconstruction performance for different PSF parameters suggests its potential for mass 3D reconstruction of LFM data.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The codes, the documentation and example data are available on an open source at: https:\/\/github.com\/Onetism\/AutoDeconJ.git.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac760","type":"journal-article","created":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T13:30:50Z","timestamp":1669642250000},"source":"Crossref","is-referenced-by-count":8,"title":["AutoDeconJ: a GPU-accelerated ImageJ plugin for 3D light-field deconvolution with optimal iteration numbers predicting"],"prefix":"10.1093","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1597-6244","authenticated-orcid":false,"given":"Changqing","family":"Su","sequence":"first","affiliation":[{"name":"School of Mechanical, Electrical & Information Engineering, Shandong University , Weihai 264209, China"},{"name":"National Engineering Laboratory for Video Technology (NELVT), Peking University , Beijing 100871, China"}]},{"given":"Yuhan","family":"Gao","sequence":"additional","affiliation":[{"name":"Lishui Institute of Hangzhou Dianzi University , Hangzhou 323000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5319-0934","authenticated-orcid":false,"given":"You","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Electronic Science and Engineering, Nanjing University , Nanjing 210023, China"}]},{"given":"Yaoqi","family":"Sun","sequence":"additional","affiliation":[{"name":"Lishui Institute of Hangzhou Dianzi University , Hangzhou 323000, China"}]},{"given":"Chenggang","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Mechanical, Electrical & Information Engineering, Shandong University , Weihai 264209, China"},{"name":"Lishui Institute of Hangzhou Dianzi University , Hangzhou 323000, China"}]},{"given":"Haibing","family":"Yin","sequence":"additional","affiliation":[{"name":"Lishui Institute of Hangzhou Dianzi University , Hangzhou 323000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7815-3603","authenticated-orcid":false,"given":"Bo","family":"Xiong","sequence":"additional","affiliation":[{"name":"National Engineering Laboratory for Video Technology (NELVT), Peking University , Beijing 100871, China"}]}],"member":"286","published-online":{"date-parts":[[2022,11,28]]},"reference":[{"key":"2023010107515934600_btac760-B1","doi-asserted-by":"crossref","first-page":"1653","DOI":"10.1126\/science.281.5383.1653","article-title":"Design of organic molecules with large two-photon absorption cross sections","volume":"281","author":"Albota","year":"1998","journal-title":"Science"},{"key":"2023010107515934600_btac760-B2","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1109\/38.219457","article-title":"What's that deal with the DCT?","volume":"13","author":"Blinn","year":"1993","journal-title":"IEEE Comput. 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