Single-image structured illumination using Hilbert transform demodulation

Hoffman, Zachary R.; DiMarzio, Charles A.

doi:10.1117/1.jbo.22.5.056011

Cited by 9 publications

(13 citation statements)

References 16 publications

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“…Many different sectioning techniques have been developed to provide sectioning from three phases. 8,[18][19][20][21] However, as shown by Hoffman and DiMarzio, 11 the susceptibility of phase misalignment in turbid media renders most images useless. Using a random pattern, rather than one of discrete phase changes, ensures that sectioning at depth produces nominally artifact-free images.…”

Section: Sectioning Techniquesmentioning

confidence: 99%

“…This method has the benefit of not requiring exact phase shifts but also allows for in vivo imaging without any tagging. 4,11 However, without discrete frequencies and phase shifts, the original method for super-resolution, developed by Gustafsson, cannot be applied to random patterns. Thus, we develop two methods of providing both sectioning at depth and resolution enhancements using a random pattern.…”

Section: Introductionmentioning

confidence: 99%

“…(c) Random modulation pattern on a mirror, spanning the entire allowable frequency space, providing both sectioning and resolution improvement at the cost of additional data samples.Journal of Biomedical Optics116003-4 November 2017 • Vol. 22(11)…”

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confidence: 99%

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Super-resolution structured illumination in optically thick specimens without fluorescent tagging

Hoffman

DiMarzio

2017

J. Biomed. Opt

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This research extends the work of Hoffman et al. to provide both sectioning and super-resolution using random patterns within thick specimens. Two methods of processing structured illumination in reflectance have been developed without the need for a priori knowledge of either the optical system or the modulation patterns. We explore the use of two deconvolution algorithms that assume either Gaussian or sparse priors. This paper will show that while both methods accomplish their intended objective, the sparse priors method provides superior resolution and contrast against all tested targets, providing anywhere from ∼1.6× to ∼2× resolution enhancement. The methods developed here can reasonably be implemented to work without a priori knowledge about the patterns or point spread function. Further, all experiments are run using an incoherent light source, unknown random modulation patterns, and without the use of fluorescent tagging. These additional modifications are challenging, but the generalization of these methods makes them prime candidates for clinical application, providing super-resolved noninvasive sectioning in vivo.

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Section: Sectioning Techniquesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Super-resolution structured illumination in optically thick specimens without fluorescent tagging

Hoffman

DiMarzio

2017

J. Biomed. Opt

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“…To increase the speed of acquisition, some approaches have proposed to reduce the number of projected patterns. [11][12][13][14] Methods, such as single-snapshot imaging of optical properties (SSOP), make use of a single pattern of light, 11,12 and the combination of this method with temporal encoding of the wavelengths has been proposed to achieve rapid multispectral acquisitions. 15,16 However, these approaches still make use of standard camera-based technology such as complementary metal-oxide-semiconductor (CMOS) or charge-coupled device (CCD) sensors that are generally expensive, monochromatic, limited in dynamic range, and importantly are limiting for multiand hyperspectral imaging configurations.…”

Section: Introductionmentioning

confidence: 99%

Single snapshot imaging of optical properties using a single-pixel camera: a simulation study

et al. 2019

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We present the effects of using a single-pixel camera approach to extract optical properties with the single-snapshot spatial frequency-domain imaging method. We acquired images of a human hand for spatial frequencies ranging from 0.1 to 0.4 mm −1 with increasing compression ratios using adaptive basis scan wavelet prediction strategy. In summary, our findings indicate that the extracted optical properties remained usable up to 99% of compression rate at a spatial frequency of 0.2 mm −1 with errors of 5% in reduced scattering and 10% in absorption.

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“…These papers are, "Structured illumination microscopy using random intensity incoherent reflectance", "Single-image structured illumination using Hilbert transform demodulation", and "Super-resolution structured illumination in optically thick specimens without fluorescent tagging". 15,16 Four talks were also given at the SPIE conference Photonics west, two of which, were based on the methods developed in our previously published papers. Additionally, a talk was given in collaboration with students from UAndes in Santiago, Chile, based on the combination of structured illumination and laser speckle contrast imaging.…”

Section: Introductionmentioning

confidence: 99%

Structured illumination for in-vivo sectioning and imaging

Hoffman¹

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Structured illumination microscopy (SIM) is a method of non-invasively extracting depth information about a specimen. By using modulated light focused at a discrete depth, it is able optically section a single plane of focus, even in the presence of scattered light from other, out-of-focus planes. However, in order for images to be accurately extracted, the modulation pattern must be positioned into three discrete phases, whose alignment is critical to artifact-free reconstruction. Due to this constraint, SIM does not work well at depth, within optically turbid media, such as human skin. Our research considers two new methods of applying and processing SIM. Random modulation patterns are considered which do not rely on discrete phase differences and are therefore much more robust at depth. In parallel, a complimentary super-resolution method is applied to extract both depth information, as well as enhanced resolution that exceeds the diffraction limit of the system. Secondly, a new single image processing scheme, based on the Hilbert transform is developed to process traditional discrete frequency, modulation patterns. This method mitigates the need for phase alignment greatly increasing the depth of the sectioning, as well as allowing for real-time processing. Further, we produce these images using an LED source in reflectance, obviating the need for fluorescent markers, which we are able to demonstrate by producing in-vivo images on a human subject. This research extends the depth of SIM to ∼100um within a tissue sample bringing it much closer to other clinical tools, such as Confocal, at a fraction of the cost. i 11 Dissertation Conclusion 122 v List of Figures Diagram outlining a typical Confocal reflectance system. This only shows the pin-hole system, which needs to be scanned in the X and Y directions to build a full two dimensional image.. .. 2 Diagram demonstrating the high frequency modulation pattern at the focal plane. Regions above and below the focal plane quickly go out of focus, removing the modulation pattern.. .. .. . .

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Single-image structured illumination using Hilbert transform demodulation

Cited by 9 publications

References 16 publications

Super-resolution structured illumination in optically thick specimens without fluorescent tagging

Super-resolution structured illumination in optically thick specimens without fluorescent tagging

Single snapshot imaging of optical properties using a single-pixel camera: a simulation study

Structured illumination for in-vivo sectioning and imaging

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