Holographic deep learning for rapid optical screening of anthrax spores

Science Advances

Volumn 3, Issue 8, 2017, Pages

  Jo, YoungJu ^a   Park, Sangjin ^a,b   Jung, JaeHwang ^a   Yoon, Jonghee ^a   Joo, Hosung ^a   Kim, Min Hyeok ^a   Kang, Suk Jo ^a   Choi, Myung Chul ^a   Lee, Sang Yup ^a   Park, YongKeun ^a,c  

^a Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

^b Agency for Defence Development   (South Korea)

^c Yuseong gu   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

BACTERIOLOGY; DEEP NEURAL NETWORKS; DIAGNOSIS; DISEASES; HOLOGRAPHY; NEURAL NETWORKS; PATHOGENS;

BACILLUS ANTHRACIS SPORES; BIOCHEMICAL METHODS; CONVOLUTIONAL NEURAL NETWORK; EARLY WARNING SYSTEM; HOLOGRAPHIC MICROSCOPY; LIMITED SENSITIVITY; LISTERIA MONOCYTOGENES; PRE-PROCESSING STEP;

DEEP LEARNING;

ALGORITHM; ANTHRAX; BACILLUS ANTHRACIS; BACTERIAL SPORE; CYTOLOGY; DATA ANALYSIS; DEVICES; HOLOGRAPHY; HUMAN; IMAGE PROCESSING; MACHINE LEARNING; MICROBIOLOGY; MICROSCOPY; PROCEDURES;

ALGORITHMS; ANTHRAX; BACILLUS ANTHRACIS; DATA ANALYSIS; DEEP LEARNING; HOLOGRAPHY; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MACHINE LEARNING; MICROSCOPY; SPORES, BACTERIAL;

EID: 85035768626     PISSN: None     EISSN: 23752548     Source Type: Journal    
DOI: 10.1126/sciadv.1700606     Document Type: Article

References (52)

1. P. S. Brachman, Bioterrorism: An update with a focus on anthrax. Am. J. Epidemiol. 155, 981-987 (2002).
2. D. R. Walt, D. R. Franz, Peer reviewed: Biological warfare detection. Anal. Chem. 72, 738A-746A (2000).
3. D. King, V. Luna, A. Cannons, J. Cattani, P. Amuso, Performance assessment of three commercial assays for direct detection of Bacillus anthracis spores. J. Clin. Microbiol. 41, 3454-3455 (2003).
4. W. Hurtle, E. Bode, D. A. Kulesh, R. S. Kaplan, J. Garrison, D. Bridge, M. House, M. S. Frye, B. Loveless, D. Norwood, Detection of the Bacillus anthracis gyrA gene by using a minor groove binder probe. J. Clin. Microbiol. 42, 179-185 (2004).
5. X. Zhang, M. A. Young, O. Lyandres, R. P. Van Duyne, Rapid detection of an anthrax biomarker by surface-enhanced Raman spectroscopy. J. Am. Chem. Soc. 127, 4484-4489 (2005).
6. B. Javidi, I. Moon, S. Yeom, E. Carapezza, Three-dimensional imaging and recognition of microorganism using single-exposure on-line (SEOL) digital holography. Opt. Express 13, 4492-4506 (2005).
7. I. Moon, B. Javidi, Three-dimensional identification of stem cells by computational holographic imaging. J. R. Soc. Interface 4, 305-313 (2007).
8. I. Moon, B. Javidi, 3-D visualization and identification of biological microorganisms using partially temporal incoherent light in-line computational holographic imaging. IEEE Trans. Med. Imaging 27, 1782-1790 (2008).
9. I. Moon, M. Daneshpanah, B. Javidi, A. Stern, Automated three-dimensional identification and tracking of micro/nanobiological organisms by computational holographic microscopy. Proc. IEEE 97, 990-1010 (2009).
10. B. Javidi, M. Daneshpanah, I. Moon, Three-dimensional holographic imaging for identification of biological micro/nanoorganisms. IEEE Photonics J. 2, 256-259 (2010).
11. I. Moon, M. Daneshpanah, A. Anand, B. Javidi, Cell identification computational 3-D holographic microscopy. Opt. Photonics News 22, 18-23 (2011).
12. A. Anand, V. Chhaniwal, N. Patel, B. Javidi, Automatic identification of malaria-infected RBC with digital holographic microscopy using correlation algorithms. IEEE Photonics J. 4, 1456-1464 (2012).
13. I. Moon, A. Anand, M. Cruz, B. Javidi, Identification of Malaria-infected red blood cells via digital shearing interferometry and statistical inference. IEEE Photonics J. 5, 6900207 (2013).
14. A. Anand, I. Moon, B. Javidi, Automated disease identification with 3-D optical imaging: A medical diagnostic tool. Proc. IEEE 105, 924-946 (2017).
15. Y. Jo, J. H. Jung, M.-h. Kim, H. J. Park, S.-J. Kang, Y. K. Park, Label-free identification of individual bacteria using Fourier transform light scattering. Opt. Express 23, 15792-15805 (2015).
16. D. Vercruysse, A. Dusa, R. Stahl, G. Vanmeerbeeck, K. de Wijs, C. Liu, D. Prodanov, P. Peumansa, L. Lagae, Three-part differential of unlabeled leukocytes with a compact lens-free imaging flow cytometer. Lab Chip 15, 1123-1132 (2015).
17. C. L. Chen, A. Mahjoubfar, L.-C. Tai, I. K. Blaby, A. Huang, K. R. Niazi, B. Jalali, Deep learning in label-free cell classification. Sci. Rep. 6, 21471 (2016).
18. H. S. Park, M. T. Rinehart, K. A. Walzer, J.-T. A. Chi, A. Wax, Automated detection of P. falciparum using machine learning algorithms with quantitative phase images of unstained cells. PLOS ONE 11, e0163045 (2016).
19. K. Lee, K. Kim, J. Jung, J. H. Heo, S. Cho, S. Lee, G. Chang, Y. J. Jo, H. Park, Y. K. Park, Quantitative phase imaging techniques for the study of cell pathophysiology: From principles to applications. Sensors 13, 4170-4191 (2013).
20. P. Y. Liu, L. K. Chin, W. Ser, H. F. Chen, C.-M. Hsieh, C.-H. Lee, K.-B. Sung, T. C. Ayi, P. H. Yap, B. Liedberg, K. Wang, T. Bourouinaj, Y. Leprince-Wang, Cell refractive index for cell biology and disease diagnosis: Past, present and future. Lab Chip 16, 634-644 (2016).
21. Y. LeCun, Y. Bengio, G. Hinton, Deep learning. Nature 521, 436-444 (2015).
22. S. Haykin, Neural Networks and Learning Machines (Pearson, 2009), vol. 3.
23. Y. Jo, J. H. Jung, J. W. Lee, D. Shin, H. J. Park, K. T. Nam, J.-H. Park, Y. K. Park, Angle-resolved light scattering of individual rod-shaped bacteria based on Fourier transform light scattering. Sci. Rep. 4, 5090 (2014).
24. B. D. Green, L. Battisti, T. M. Koehler, C. B. Thorne, B. E. Ivins, Demonstration of a capsule plasmid in Bacillus anthracis. Infect. Immun. 49, 291-297 (1985).
25. O. A. Økstad, A.-B. Kolstø, Genomics of Bacillus species, in Genomics of Foodborne Bacterial Pathogens, M. Wiedmann, W. Zhang, Eds. (Springer, 2011), pp. 29-53.
26. E. Helgason, O. A. Økstad, D. A. Caugant, H. A. Johansen, A. Fouet, M. Mock, I. Hegna, A.-B. Kolstø, Bacillus anthracis, Bacillus cereus, and Bacillus thuringiensis-One species on the basis of genetic evidence. Appl. Environ. Microbiol. 66, 2627-2630 (2000).
27. D. L. Greenberg, J. D. Busch, P. Keim, D. M. Wagner, Identifying experimental surrogates for Bacillus anthracis spores: A review. Investigative Genet. 1, 4 (2010).
28. H. S. Gibbons, S. M. Broomall, L. A. McNew, H. Daligault, C. Chapman, D. Bruce, M. Karavis, M. Krepps, P. A. McGregor, C. Hong, K. H. Park, A. Akmal, A. Feldman, J. S. Lin, W. E. Chang, B. W. Higgs, P. Demirev, J. Lindquist, A. Liem, E. Fochler, T. D. Read, R. Tapia, S. Johnson, K. A. Bishop-Lilly, C. Detter, C. Han, S. Sozhamannan, C. N. Rosenzweig, E. W. Skowronski, Genomic signatures of strain selection and enhancement in Bacillus atrophaeus var. globigii, a historical biowarfare simulant. PLOS ONE 6, e17836 (2011).
29. M. Carrera, R. Zandomeni, J. Fitzgibbon, J.-L. Sagripanti, Difference between the spore sizes of Bacillus anthracis and other Bacillus species. J. Appl. Microbiol. 102, 303-312 (2007).
30. M. Plomp, T. J. Leighton, K. E. Wheeler, A. J. Malkin, Architecture and high-resolution structure of Bacillus thuringiensis and Bacillus cereus spore coat surfaces. Langmuir 21, 7892-7898 (2005).
31. A. Krizhevsky, I. Sutskever, G. E. Hinton, ImageNet classification with deep convolutional neural networks, in Advances in Neural Information Processing Systems 25 (NIPS 2012) (NIPS, 2012), pp.1097-1105.
32. L. van der Maaten, G. Hinton, Visualizing data using t-SNE. J. Mach. Learn. Res. 9, 2579-2605 (2008).
33. G. Popescu, Y. K. Park, N. Lue, C. Best-Popescu, L. Deflores, R. R. Dasari, M. S. Feld, K. Badizadegan, Optical imaging of cell mass and growth dynamics. Am. J. Physiol. Cell Physiol. 295, C538-C544 (2008).
34. A. O. Henriques, C. P. Moran Jr., Structure, assembly, and function of the spore surface layers. Annu. Rev. Microbiol. 61, 555-588 (2007).
35. D. A. Ball, R. Taylor, S. J. Todd, C. Redmond, E. Couture-Tosi, P. Sylvestre, A. Moir, P. A. Bullough, Structure of the exosporium and sublayers of spores of the Bacillus cereus family revealed by electron crystallography. Mol. Microbiol. 68, 947-958 (2008).
36. M. Carrera, R. O. Zandomeni, J.-L. Sagripanti, Wet and dry density of Bacillus anthracis and other Bacillus species. J. Appl. Microbiol. 105, 68-77 (2008).
37. J. Low, W. Donachie, A review of Listeria monocytogenes and listeriosis. Vet. J. 153, 9-29 (1997).
38. V. R. Després, J. A. Huffman, S. M. Burrows, C. Hoose, A. S. Safatov, G. Buryak, J. Fröhlich-Nowoisky, W. Elbert, M. O. Andreae, U. Pöschl, R. Jaenicke, Primary biological aerosol particles in the atmosphere: A review. Tellus B 64, 15598 (2012).
39. J.-H. Jung, J. Jang, Y. Park, Spectro-refractometry of individual microscopic objects using swept-source quantitative phase imaging. Anal. Chem. 85, 10519-10525 (2013).
40. Y. Kim, J. Jeong, J. Jang, M. W. Kim, Y. Park, Polarization holographic microscopy for extracting spatio-temporally resolved Jones matrix. Opt. Express 20, 9948-9955 (2012).
41. K. Kim, H. O. Yoon, M. Diez-Silva, M. Dao, R. R. Dasari, Y. K. Park, High-resolution three-dimensional imaging of red blood cells parasitized by Plasmodium falciparum and in situ hemozoin crystals using optical diffraction tomography. J. Biomed. Opt. 19, 011005 (2013).
42. A. Yousten, M. Rogoff, Metabolism of Bacillus thuringiensis in relation to spore and crystal formation. J. Bacteriol. 100, 1229-1236 (1969).
43. S. K. Debnath, Y. Park, Real-time quantitative phase imaging with a spatial phase-shifting algorithm. Opt. Lett. 36, 4677-4679 (2011).
44. D. H. Hubel, T. N. Wiesel, Receptive fields of single neurones in the cat's striate cortex. J. Physiol. 148, 574-591 (1959).
45. K. Lee, H.-D. Kim, K. Kim, Y. Kim, T. R. Hillman, B. Min, Y. K. Park, Synthetic Fourier transform light scattering. Opt. Express 21, 22453-22463 (2013).
46. R. Barer, Interference microscopy and mass determination. Nature 169, 366-367 (1952).
47. M. Godin, F. F. Delgado, S. Son, W. H. Grover, A. K. Bryan, A. Tzur, P. Jorgensen, K. Payer, A. D. Grossman, M. W. Kirschner, S. R. Manalis, Using buoyant mass to measure the growth of single cells. Nat. Methods 7, 387-390 (2010).
48. A. Vedaldi, K. Lenc, MatConvNet: Convolutional neural networks for MATLAB, in Proceedings of the 23rd ACM International Conference on Multimedia (ACM, 2015), pp. 689-692.
49. V. Nair, G. E. Hinton, Rectified linear units improve restricted Boltzmann machines, in Proceedings of the 27th International Conference on Machine Learning (ICML 2010) (ICML, 2010), pp. 807-814.
50. N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, R. Salakhutdinov, Dropout: A simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15, 1929-1958 (2014).
51. S. Ioffe, C. Szegedy, Batch normalization: Accelerating deep network training by reducing internal covariate shift, in Proceedings of the 32nd International Conference on Machine Learning (ICML 2015) (ICML, 2015), pp. 448-456.
52. K. He, X. Zhang, S. Ren, J. Sun, Delving deep into rectifiers: Surpassing human-level performance on ImageNet classification, in Proceedings of the IEEE International Conference on Computer Vision (ICCV) (IEEE, 2015), pp. 1026-1034.