Jason T. Smith, Nathan Un, Ruoyang Yao, Nattawut Sinsuebphon, Alena Rudkouskaya, J. Mazurkiewicz, Margarida M Barroso, Pingkun Yan, X. Intes
{"title":"Fluorescent Lifetime Imaging improved via Deep Learning","authors":"Jason T. Smith, Nathan Un, Ruoyang Yao, Nattawut Sinsuebphon, Alena Rudkouskaya, J. Mazurkiewicz, Margarida M Barroso, Pingkun Yan, X. Intes","doi":"10.1364/ntm.2019.nm3c.4","DOIUrl":null,"url":null,"abstract":"Herein, we present a novel workflow based on Deep Learning (DL) trained on synthetic data to quantify fluorescence lifetime imaging of experimental data across multiple microscopic and macroscopic applications with unprecedented accuracy and computational speed.","PeriodicalId":8973,"journal":{"name":"Biophotonics Congress: Optics in the Life Sciences Congress 2019 (BODA,BRAIN,NTM,OMA,OMP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biophotonics Congress: Optics in the Life Sciences Congress 2019 (BODA,BRAIN,NTM,OMA,OMP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/ntm.2019.nm3c.4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Herein, we present a novel workflow based on Deep Learning (DL) trained on synthetic data to quantify fluorescence lifetime imaging of experimental data across multiple microscopic and macroscopic applications with unprecedented accuracy and computational speed.