7,550 research outputs found
Computational localization microscopy with extended axial range
A new single-aperture 3D particle-localization and tracking technique is presented that demonstrates an increase in depth range by more than an order of magnitude without compromising optical resolution and throughput. We exploit the extended depth range and depth-dependent translation of an Airy-beam PSF for 3D localization over an extended volume in a single snapshot. The technique is applicable to all bright-field and fluorescence modalities for particle localization and tracking, ranging from super-resolution microscopy through to the tracking of fluorescent beads and endogenous particles within cells. We demonstrate and validate its application to real-time 3D velocity imaging of fluid flow in capillaries using fluorescent tracer beads. An axial localization precision of 50 nm was obtained over a depth range of 120ÎĽm using a 0.4NA, 20Ă— microscope objective. We believe this to be the highest ratio of axial range-to-precision reported to date
Semi-Blind Spatially-Variant Deconvolution in Optical Microscopy with Local Point Spread Function Estimation By Use Of Convolutional Neural Networks
We present a semi-blind, spatially-variant deconvolution technique aimed at
optical microscopy that combines a local estimation step of the point spread
function (PSF) and deconvolution using a spatially variant, regularized
Richardson-Lucy algorithm. To find the local PSF map in a computationally
tractable way, we train a convolutional neural network to perform regression of
an optical parametric model on synthetically blurred image patches. We
deconvolved both synthetic and experimentally-acquired data, and achieved an
improvement of image SNR of 1.00 dB on average, compared to other deconvolution
algorithms.Comment: 2018/02/11: submitted to IEEE ICIP 2018 - 2018/05/04: accepted to
IEEE ICIP 201
Extended depth-of-field imaging and ranging in a snapshot
Traditional approaches to imaging require that an increase in depth of field is associated with a reduction in
numerical aperture, and hence with a reduction in resolution and optical throughput. In their seminal
work, Dowski and Cathey reported how the asymmetric point-spread function generated by a cubic-phase
aberration encodes the detected image such that digital recovery can yield images with an extended depth of
field without sacrificing resolution [Appl. Opt. 34, 1859 (1995)]. Unfortunately recovered images are
generally visibly degraded by artifacts arising from subtle variations in point-spread functions with defocus.
We report a technique that involves determination of the spatially variant translation of image components
that accompanies defocus to enable determination of spatially variant defocus. This in turn enables recovery
of artifact-free, extended depth-of-field images together with a two-dimensional defocus and range map
of the imaged scene. We demonstrate the technique for high-quality macroscopic and microscopic imaging
of scenes presenting an extended defocus of up to two waves, and for generation of defocus maps with an
uncertainty of 0.036 waves
3D differential phase contrast microscopy
We demonstrate 3D phase and absorption recovery from partially coherent intensity images captured with a programmable LED array source. Images are captured through-focus with four different illumination patterns. Using first Born and weak object approximations (WOA), a linear 3D differential phase contrast (DPC) model is derived. The partially coherent transfer functions relate the sample's complex refractive index distribution to intensity measurements at varying defocus. Volumetric reconstruction is achieved by a global FFT-based method, without an intermediate 2D phase retrieval step. Because the illumination is spatially partially coherent, the transverse resolution of the reconstructed field achieves twice the NA of coherent systems and improved axial resolution
Confocal microscopy of colloidal particles: towards reliable, optimum coordinates
Over the last decade, the light microscope has become increasingly useful as
a quantitative tool for studying colloidal systems. The ability to obtain
particle coordinates in bulk samples from micrographs is particularly
appealing. In this paper we review and extend methods for optimal image
formation of colloidal samples, which is vital for particle coordinates of the
highest accuracy, and for extracting the most reliable coordinates from these
images. We discuss in depth the accuracy of the coordinates, which is sensitive
to the details of the colloidal system and the imaging system. Moreover, this
accuracy can vary between particles, particularly in dense systems. We
introduce a previously unreported error estimate and use it to develop an
iterative method for finding particle coordinates. This individual-particle
accuracy assessment also allows comparison between particle locations obtained
from different experiments. Though aimed primarily at confocal microscopy
studies of colloidal systems, the methods outlined here should transfer readily
to many other feature extraction problems, especially where features may
overlap one another.Comment: Accepted by Advances in Colloid and Interface Scienc
3D deconvolution in Fourier integral microscopy
Fourier integral microscopy (FiMic), also referred to as Fourier light field microscopy (FLFM) in the literature, was recently proposed as an alternative to conventional light field microscopy (LFM). FiMic is designed to overcome the non-uniform lateral resolution limitation specific to LFM. By inserting a micro-lens array at the aperture stop of the microscope objective, the Fourier integral microscope directly captures in a single-shot a series of orthographic views of the scene from different viewpoints. We propose an algorithm for the deconvolution of FiMic data by combining the well known Maximum Likelihood Expectation (MLEM) method with total variation (TV) regularization to cope with noise amplification in conventional Richardson-Lucy deconvolution
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