Skip to main content Accessibility help
×
  1. Home
  2. Browse subjects
  3. Engineering
  4. Biomedical engineering
  5. Content listing

Refine search

Refine search

Access:
Content type:
Publication date:
Apply   From and To filters
Subject: Show more
Journals Show more
Publishers: Show more
Societies Show more
Series: Show more
Collections: Show more

Actions for selected content:

Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Save to Kindle
  • Save to Dropbox
  • Save to Google Drive

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
Cancel
×

1869 results in Biomedical engineering

Page 15 of 94

  • 15 - Shaped Beams for Light Sheet Imaging and Optical Manipulation

  • from Part VI - Shaped Beams for Light Sheet Microscopy
  • Edited by Joel Kubby, University of California, Santa Cruz, Sylvain Gigan, Meng Cui, Purdue University, Indiana
  • Book:
    Wavefront Shaping for Biomedical Imaging
    Published online:
    10 June 2019
    Print publication:
    20 June 2019, pp 358-378

  • Summary

    This chapter covers three main advanced themes in light sheet imaging. Firstly, we discuss the widely recognized issues of sample induced optical aberrations. In itself this is broad and topical area given the importance of probing deeper into biological systems. This requirement arises as we wish to gain functional imaging which often can only be gleamed at depths currently difficult to attain (e.g. > 1 mm). The scattering and absorptive properties of tissue compromise contrast in thick tissue. This issues is exacerbated in fluorescence light sheet microscopy for which the fluorescence excitation and detection paths do not coincide. In this chapter we discuss different approaches to adaptive aberration measurement and correction of both the illumination and the detection paths for deep tissue light sheet microscopy.

  • 1 - Adaptive Optical Microscopy Using Image-Based Wavefront Sensing

  • from Part I - Adaptive Optical Microscopy for Biological Imaging
  • Edited by Joel Kubby, University of California, Santa Cruz, Sylvain Gigan, Meng Cui, Purdue University, Indiana
  • Book:
    Wavefront Shaping for Biomedical Imaging
    Published online:
    10 June 2019
    Print publication:
    20 June 2019, pp 3-21

  • Summary

    The general approach to wavefront sensorless adaptive optics (or “sensorless AO” for short) relies upon the optimisation of a measurement that is known to be related to the aberration content. For example, in an adaptive laser focussing system, one might maximise the intensity at the centre of the focussed beam. In image-based AO systems, which are a sub-category of sensorless AO systems, an appropriately chosen image property is optimised. In certain microscopes (e.g. confocal or multi-photon microscopes) the total image intensity (sum of all pixel values) is an appropriate optimisation metric, as it exhibits a maximum value when no aberration is present. If the aberration in the system is non-zero due to refractive index variations in the specimen, then the value of the metric will be lower than its optimal value. The goal of the sensorless AO routine would be to use the adaptive element to maximise the metric by minimising the total aberration in the system.

  • 16 - Incoherent Illumination Tomography and Adaptive Optics

  • from Part VII - Tomography
  • Edited by Joel Kubby, University of California, Santa Cruz, Sylvain Gigan, Meng Cui, Purdue University, Indiana
  • Book:
    Wavefront Shaping for Biomedical Imaging
    Published online:
    10 June 2019
    Print publication:
    20 June 2019, pp 381-403

  • Summary

    Optical tomography techniques have been widely used for imaging. Among those techniques, since its development optical coherence tomography (OCT) has played an important role in imaging biological samples, especially in eye examinations. The combination of OCT with adaptive optics (AO) for aberration correction to improve the OCT performance is one of the most impactful technique advances for non-invasive and high resolution imaging. In this chapter, we are going to discuss about an en face approach of OCT, Full-Field OCT or FFOCT, and about a compact AO-FFOCT system that was coupled with a transmissive liquid crystal spatial light modulator (LCSLM) to induce or correct aberrations. We will show that, with spatially incoherent illumination, the FFOCT system point spread function (PSF) is almost independent of aberrations that mostly induce a reduction of the signal level (signal to noise ratio) without broadening the PSF width. By comparing scanning OCT with spatially coherent illumination, wide-field OCT with spatially coherent illumination and FFOCT with spatially incoherent illumination, theoretical analysis, numerical calculation as well as experimental results are demonstrated to show this specific merit of incoherent illumination in FFOCT. We will also demonstrate a compact AO-FFOCT system in which the strict pupil conjugation is abandoned for low order aberrations correction. A wavefront sensorless method is used for distortion compensation by using the FFOCT signal as the metric based on the resolution conservation property of FFOCT. AO experiment results done with USAF resolution target and biological samples will be reviewed. And the potential of this AO-FFOCT system for retinal imaging will be discussed.

  • 4 - Zonal Adaptive Optical Microscopy for Deep Tissue Imaging

  • from Part II - Deep Tissue Microscopy
  • Edited by Joel Kubby, University of California, Santa Cruz, Sylvain Gigan, Meng Cui, Purdue University, Indiana
  • Book:
    Wavefront Shaping for Biomedical Imaging
    Published online:
    10 June 2019
    Print publication:
    20 June 2019, pp 91-118

  • Summary

    To use the visible fluorescent signal for wavefront sensing in scattering tissue at depth, we need to employ indirect wavefront sensing methods. In this section, we describe a pupil-segmentation AO method based on physical principles similar to those utilized by SH sensors. A zonal approach by nature, it differs from the wavefront measurement scheme in a SH sensor in that, rather than measuring the wavefront segments in parallel and thus being susceptible to tissue scattering as in a SH sensor, it measures the wavefront segments serially, making it applicable to strongly scattering samples such as the mouse brain.

  • 10 - Computer-Generated Holographic Techniques to Control Light Propagating through Scattering Media Using a Digital-Mirror-Device Spatial Light Modulator

  • from Part IV - Focusing Light through Turbid Media Using Feedback Optimization
  • Edited by Joel Kubby, University of California, Santa Cruz, Sylvain Gigan, Meng Cui, Purdue University, Indiana
  • Book:
    Wavefront Shaping for Biomedical Imaging
    Published online:
    10 June 2019
    Print publication:
    20 June 2019, pp 240-254

  • Summary

    This chapter reviews the advances in light control through complex media using a DMD. Although these devices are known for their amplitude modulation capabilities, the implementation of binary holographic techniques effectively converts them into phase modulation devices. The fast decorrelation time of tissue, in the milliseconds time scale, motivates the research and development of fast focusing and imaging methods. The main advantage of using these MEMS devices, is the high switching speed, up to more than 20 kHz, improving the bandwidth with respect to the widely used LC-SLMs. DMDs have allowed reducing the total focusing time through complex media to tens of milliseconds, close to the speckle decorrelation times of dynamic biological media (tissue). The signal-to-noise ratio (SNR) of the signal detected is critical in this type of high-speed experiment because SNR decreases with the integration time. Therefore, the implementation of algorithms designed for low SNR environments will be required in the future.

  • 9 - Focusing Light through Scattering Media Using a Microelectromechanical Systems Spatial Light Modulator

  • from Part IV - Focusing Light through Turbid Media Using Feedback Optimization
  • Edited by Joel Kubby, University of California, Santa Cruz, Sylvain Gigan, Meng Cui, Purdue University, Indiana
  • Book:
    Wavefront Shaping for Biomedical Imaging
    Published online:
    10 June 2019
    Print publication:
    20 June 2019, pp 217-239

  • Summary

    In this chapter, we describe the use of a MEMS device to enhance microscopic focusing in scattering media. We begin the chapter with the manufacturing and actuation mechanism of MEMS SLMs. Then we illustrate how focusing through scattering media is achieved using both monochromatic and chromatic light. In recent development, two- and three-photon microscopy is demonstrated with MEMS SLMs for scattered light control. Lastly, conjugate AO is provided as future direction to the readers to overcome field of view limitations most for subsurface imaging applications.

  • 6 - Coupling Optical Wavefront Shaping and Photoacoustics

  • from Part III - Focusing Light through Turbid Media Using the Scattering Matrix
  • Edited by Joel Kubby, University of California, Santa Cruz, Sylvain Gigan, Meng Cui, Purdue University, Indiana
  • Book:
    Wavefront Shaping for Biomedical Imaging
    Published online:
    10 June 2019
    Print publication:
    20 June 2019, pp 138-160

  • Summary

    In this chapter, we introduce and review recent research works based on the coupling optical wavefront shaping and photoacoustics. Coupling these two research fields, that have until recently developed rather independently, offers mutual advantages for both fields: on the one hand, the photocoustic effect provides a powerful sensing mechanism for optical wavefront shaping techniques, while on the other hand photoacoustic imaging can greatly benefit from optical wavefront shaping techniques. This chapter first introduces the principle of photoacoustics relevant in the context of this chapter, including an introduction to the photoacoustic effect and a brief overview of the principles of biomedical photoacoustic imaging. We then first review the recent works on photoacoustic-guided optical wavefront shaping, either with optimization or transmission-matrix approaches, and finally illustrate how optical wavefront shaping can be applied to develop minimally invasive photoacoustic microendscopy mith multimode fibers. Some parts of this chapter have been adapted from a recent review article on coupling photoacoustics and coherent light [1].

  • 2 - Adaptive Optical Microscopy Using Guide Star–Based Direct Wavefront Sensing

  • from Part I - Adaptive Optical Microscopy for Biological Imaging
  • Edited by Joel Kubby, University of California, Santa Cruz, Sylvain Gigan, Meng Cui, Purdue University, Indiana
  • Book:
    Wavefront Shaping for Biomedical Imaging
    Published online:
    10 June 2019
    Print publication:
    20 June 2019, pp 22-58

  • Summary

    We review adaptive optics (AO) in biological imaging using direct wavefront measurement. Here light from a point source in the specimen is used to measure the wavefront with a detector such as a Shack-Hartmann wavefront sensor, similar to the approach that is used in astronomy. The benefit of direct wavefront measurement relative to the sensorless methods is that the wavefront can be measured quickly in one step. Typically sensorless methods are iterative, requiring a number of measurements. Taking multiple measurements can take more time and may expose the sample to more light which can lead to photo-bleaching. Another benefit is that some indirect methods use optimization of a merit function such as image sharpness or image intensity. In direct wavefront sensing the wavefront aberration is directly measured and corrected rather than optimized. As we shall discuss, a common metric for direct wavefront measurement and correction is the Strehl ratio which is defined as the ratio of the on-axis beam intensity to the diffraction limited beam intensity. The objective is getting as close as possible to the diffraction limit.

  • 17 - Computational Adaptive Optics for Broadband Optical Interferometric Tomography of Biological Tissue

  • from Part VII - Tomography
  • Edited by Joel Kubby, University of California, Santa Cruz, Sylvain Gigan, Meng Cui, Purdue University, Indiana
  • Book:
    Wavefront Shaping for Biomedical Imaging
    Published online:
    10 June 2019
    Print publication:
    20 June 2019, pp 404-422

  • Summary

    In addition to the many hardware methods for wavefront shaping described in the previous chapters, it is also possible to modify the wavefront computationally. Using interferometric detection, the complex optical wavefront can be measured. The phase of the wavefront can then be adjusted in software in a method analogous to that of a deformable mirror. This method is termed digital adaptive optics or computational adaptive optics (CAO). This is distinct from a previously published method of the same name which used ray tracing to guide amplitude deconvolution of 3-D datasets.

  • 3 - Deep Tissue Fluorescence Microscopy

  • from Part II - Deep Tissue Microscopy
  • Edited by Joel Kubby, University of California, Santa Cruz, Sylvain Gigan, Meng Cui, Purdue University, Indiana
  • Book:
    Wavefront Shaping for Biomedical Imaging
    Published online:
    10 June 2019
    Print publication:
    20 June 2019, pp 61-91

  • Summary

    As the signal in multiphoton microscopy inherently has nonlinear dependence on light intensity (e.g. second order nonlinearity in two-photon excitation, third order nonlinearity in three-photon excitation), the combination of nonlinearity and iterative feedback is expected to work well in practice. We named this method Iterative Multi-Photon Adaptive Compensation Technique (IMPACT).

  • 13 - Transmission Matrix Correlations

  • from Part V - Time Reversal, Optical Phase Conjugation
  • Edited by Joel Kubby, University of California, Santa Cruz, Sylvain Gigan, Meng Cui, Purdue University, Indiana
  • Book:
    Wavefront Shaping for Biomedical Imaging
    Published online:
    10 June 2019
    Print publication:
    20 June 2019, pp 315-328

  • Summary

    In this Chapter, we introduce several methods capable of focusing light deep inside scattering media noninvasively, without invasively implanting guide stars. The first method—time-reversed ultrasonically encoded (TRUE) light focusing—uses focused ultrasound as the guide star, and selectively phase-conjugates light whose frequency is acousto-optically shifted. The focal spot size is acoustic-diffraction-limited, and can be further reduced. The second method—time-reversed adapted perturbation (TRAP) light focusing—detects perturbation in the scattered light due to dynamic objects, and focuses by subsequent OPC. This method can reach optical-diffraction-limited focus because the focus tracks the dynamic object. The third method—ultrasonically encoded wavefront shaping (SEWS)—uses focused ultrasound as a guide star, which tags light via the acousto-optic effect as WFS feedback to reach an acoustic-diffraction-limited focal spot size. The last method— photoacoustically guided wavefront shaping (PAWS)—employs nonlinear photoacoustic signals as the feedback for WFS to achieve optical-diffraction-limited focusing .

Wavefront Shaping for Biomedical Imaging
  • Edited by Joel Kubby, Sylvain Gigan, Meng Cui
  • Published online:
    10 June 2019
    Print publication:
    20 June 2019
  • Learn about the theory, techniques and applications of wavefront shaping in biomedical imaging using this unique text. With authoritative contributions from researchers who are defining the field, cutting-edge theory is combined with real-world practical examples, experimental data and the latest research trends to provide the first book-level treatment of the subject. It is suitable for both background reading and use in a course, with coverage of essential topics such as adaptive optical microscopy, deep tissue microscopy, time reversal and optical phase conjugation, and tomography. The latest images from the forefront of biomedical imaging are included, and full-colour versions are available in the eBook version. Researchers, practitioners and graduate students in optics, biophotonics, biomedical engineering, and biology who use biomedical imaging tools and are looking to advance their knowledge of the subject will find this an indispensable resource.

Page 15 of 94