Intensity Weighted Subtraction Microscopy Approach for Image Contrast and Resolution Enhancement

We propose and demonstrate a novel subtraction microscopy algorithm, exploiting fluorescence emission difference or switching laser mode and their derivatives for image enhancement. The key novelty of the proposed approach lies in the weighted subtraction coefficient, adjusted pixel-by-pixel with respect to the intensity distributions of initial images. This method produces significant resolution enhancement and minimizes image distortions. Our theoretical and experimental studies demonstrate that this approach can be applied to any optical microscopy techniques, including label free and non-linear methods, where common super-resolution techniques cannot be used

Multimode fibre:Light-sheet microscopy at the tip of a needle

We also thank the UK Engineering and Physics Sciences Research Council for funding under grant EP/J01771X/1. Finally, we would like to thank EXCELLENT TEAMS (CZ.1.07/2.3.00/30.0005) from European Social Fund and CEITEC - Central European Institute of Technology (CZ.1.05/1.1.00/02.0068) from European Regional Development Fund for support.Light-sheet fluorescence microscopy has emerged as a powerful platform for 3-D volumetric imaging in the life sciences. Here, we introduce an important step towards its use deep inside biological tissue. Our new technique, based on digital holography, enables delivery of the light-sheet through a multimode optical fibre - an optical element with extremely small footprint, yet permitting complex control of light transport processes within. We show that this approach supports some of the most advanced methods in light-sheet microscopy: by taking advantage of the cylindrical symmetry of the fibre, we facilitate the wavefront engineering methods for generation of both Bessel and structured Bessel beam plane illumination. Finally, we assess the quality of imaging on a sample of fluorescent beads fixed in agarose gel and we conclude with a proof-of-principle imaging of a biological sample, namely the regenerating operculum prongs of Spirobranchus lamarcki.Publisher PDFPeer reviewe

Scalar and vector Slepian functions, spherical signal estimation and spectral analysis

It is a well-known fact that mathematical functions that are timelimited (or spacelimited) cannot be simultaneously bandlimited (in frequency). Yet the finite precision of measurement and computation unavoidably bandlimits our observation and modeling scientific data, and we often only have access to, or are only interested in, a study area that is temporally or spatially bounded. In the geosciences we may be interested in spectrally modeling a time series defined only on a certain interval, or we may want to characterize a specific geographical area observed using an effectively bandlimited measurement device. It is clear that analyzing and representing scientific data of this kind will be facilitated if a basis of functions can be found that are "spatiospectrally" concentrated, i.e. "localized" in both domains at the same time. Here, we give a theoretical overview of one particular approach to this "concentration" problem, as originally proposed for time series by Slepian and coworkers, in the 1960s. We show how this framework leads to practical algorithms and statistically performant methods for the analysis of signals and their power spectra in one and two dimensions, and, particularly for applications in the geosciences, for scalar and vectorial signals defined on the surface of a unit sphere.Comment: Submitted to the 2nd Edition of the Handbook of Geomathematics, edited by Willi Freeden, Zuhair M. Nashed and Thomas Sonar, and to be published by Springer Verlag. This is a slightly modified but expanded version of the paper arxiv:0909.5368 that appeared in the 1st Edition of the Handbook, when it was called: Slepian functions and their use in signal estimation and spectral analysi