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      Holographic deep learning for rapid optical screening of anthrax spores

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          Abstract

          A synergistic application of holography and deep learning enables rapid optical screening of anthrax spores and other pathogens.

          Abstract

          Establishing early warning systems for anthrax attacks is crucial in biodefense. Despite numerous studies for decades, the limited sensitivity of conventional biochemical methods essentially requires preprocessing steps and thus has limitations to be used in realistic settings of biological warfare. We present an optical method for rapid and label-free screening of Bacillus anthracis spores through the synergistic application of holographic microscopy and deep learning. A deep convolutional neural network is designed to classify holographic images of unlabeled living cells. After training, the network outperforms previous techniques in all accuracy measures, achieving single-spore sensitivity and subgenus specificity. The unique “representation learning” capability of deep learning enables direct training from raw images instead of manually extracted features. The method automatically recognizes key biological traits encoded in the images and exploits them as fingerprints. This remarkable learning ability makes the proposed method readily applicable to classifying various single cells in addition to B. anthracis, as demonstrated for the diagnosis of Listeria monocytogenes, without any modification. We believe that our strategy will make holographic microscopy more accessible to medical doctors and biomedical scientists for easy, rapid, and accurate point-of-care diagnosis of pathogens.

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              Primary biological aerosol particles in the atmosphere: a review

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                Author and article information

                Journal
                Sci Adv
                Sci Adv
                SciAdv
                advances
                Science Advances
                American Association for the Advancement of Science
                2375-2548
                August 2017
                04 August 2017
                : 3
                : 8
                : e1700606
                Affiliations
                [1 ]Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
                [2 ]Department of Chemical and Biomolecular Engineering (BK21 Plus Program), KAIST, Daejeon 34141, Republic of Korea.
                [3 ]Agency for Defense Development (ADD), Daejeon 34186, Republic of Korea.
                [4 ]School of Electrical Engineering, KAIST, Daejeon 34141, Republic of Korea.
                [5 ]Department of Biological Sciences, KAIST, Daejeon 34141, Republic of Korea.
                [6 ]Department of Bio and Brain Engineering, KAIST, Daejeon 34141, Republic of Korea.
                [7 ]Tomocube Inc., Daejeon 34051, Republic of Korea.
                Author notes
                [*]

                These authors contributed equally to this work.

                []Corresponding author. Email: leesy@ 123456kaist.ac.kr (S.Y.L.); yk.park@ 123456kaist.ac.kr (Y.P.)
                Author information
                http://orcid.org/0000-0001-8826-6177
                http://orcid.org/0000-0003-0599-3091
                Article
                1700606
                10.1126/sciadv.1700606
                5544395
                28798957
                4692f84b-de56-40f3-ac20-6162fec72bc6
                Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

                History
                : 27 February 2017
                : 29 June 2017
                Funding
                Funded by: doi http://dx.doi.org/10.13039/501100003725, National Research Foundation of Korea;
                Award ID: award323141
                Award ID: 2015R1A3A2066550, 2014K1A3A1A09063027, 2014M3C1A3052567
                Funded by: doi http://dx.doi.org/10.13039/501100005073, Agency for Defense Development;
                Award ID: award323140
                Award ID: ADD-14-70-06-10
                Categories
                Research Article
                Research Articles
                SciAdv r-articles
                Optical Microscopy
                Applied Sciences and Engineering
                Custom metadata
                Nova Morabe

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