• DocumentCode
    897974
  • Title

    Automated Three-Dimensional Identification and Tracking of Micro/Nanobiological Organisms by Computational Holographic Microscopy

  • Author

    Moon, Inkyu ; Daneshpanah, Mehdi ; Javidi, Bahram ; Stern, Adrian

  • Author_Institution
    Sch. of Comput. Eng., Chosun Univ., Gwangju
  • Volume
    97
  • Issue
    6
  • fYear
    2009
  • fDate
    6/1/2009 12:00:00 AM
  • Firstpage
    990
  • Lastpage
    1010
  • Abstract
    The ability to sense, track, identify, and monitor biological micro/nanoorganisms in a real-time, automated, and integrated system is of great importance from both scientific and technological standpoints. Such a system and its possible variants would have numerous applications in a wide spectrum of fields, including defense against biological warfare, disease control, environmental health and safety, and medical treatments. In this paper, we review a comprehensive mixture of optical and computational tools developed in our group aiming at real-time sensing and recognition of biological microorganisms. Digital in-line holographic microscopy is used with both coherent and partially coherent illumination to probe the specimen interferometrically. The interference pattern is then recorded on an optoelectronic image sensor and transferred to a computer where special statistical algorithms are performed to segment, recognize, and track the microorganisms within the field of view of the microscope. The advantages of proposed holographic sensing are described compared to conventional two-dimensional imaging systems. In addition, the theoretical aspects and fundamental limitations of digital in-line holographic microscopy are discussed, which determine the relationship between system parameters and achievable performance. The proposed optical-digital integrated system for automated, real-time sensing and recognition of biological microorganisms has been deemed promising with the potential of widespread application. We demonstrate how the proposed techniques function together in a series of experiments.
  • Keywords
    biomedical optical imaging; biosensors; holographic interferometry; image recognition; image segmentation; image sensors; medical image processing; microorganisms; optical microscopy; statistical analysis; automated three-dimensional identification; biological warfare; computational holographic microscopy; digital in-line holographic microscopy; disease control; environmental health; holographic sensing; interference pattern; medical treatment; microbiological organism; nanobiological organism; optical tool; optical-digital integrated system; optoelectronic image sensor; real-time sensing; statistical algorithm; Biology computing; Biomedical optical imaging; Holographic optical components; Holography; Microorganisms; Microscopy; Nanobioscience; Optical interferometry; Organisms; Real time systems; Biophotonics; Gabor feature extraction; holographic microscopy; noninvasive biosensing; three-dimensional image recognition; three-dimensional image segmentation and tracking; three-dimensional optical imaging;
  • fLanguage
    English
  • Journal_Title
    Proceedings of the IEEE
  • Publisher
    ieee
  • ISSN
    0018-9219
  • Type

    jour

  • DOI
    10.1109/JPROC.2009.2017563
  • Filename
    4939403