arXiv subjects

Krishna Agarwal

Publications and source records attributed to Krishna Agarwal.

22 records · Page 2Linked to original sources

arXiv2020

Silicon substrate significantly alters dipole-dipole resolution in coherent microscope

Influences of a substrate below samples in imaging performances are studied by reaching the solution to the dyadic Green's function, where the substrate is modeled as half space in the sample region. Then, theoretical and numerical analysis are performed in terms of magnification, depth of field, and resolution. Various settings including positions of dipoles, the distance of the substrate to the focal plane and dipole polarization are considered. Methods to measure the resolution of $z$-polarized dipoles are also presented since the modified Rayleigh limit cannot be applied directly. The silicon substrate and the glass substrate are studied with a water immersion objective lens. The high contrast between silicon and water leads to significant disturbances on imaging.

physics.optics↗

arXiv2020

Fluorescence fluctuations-based super-resolution microscopy techniques: an experimental comparative study

Fluorescence fluctuations-based super-resolution microscopy (FF-SRM) is an emerging field promising low-cost and live-cell compatible imaging beyond the resolution of conventional optical microscopy. A comprehensive overview on how the nature of fluctuations, label density, out-of-focus light, sub-cellular dynamics, and the sample itself influence the reconstruction in FF-SRM is crucial to design appropriate biological experiments. We have experimentally compared several of the recently developed FF-SRM techniques (namely ESI, bSOFI, SRRF, SACD, MUSICAL and HAWK) on widefield fluorescence image sequences of a diverse set of samples (namely liposomes, tissues, fixed and living cells), and on three-dimensional simulated data where the ground truth is available. The simulated microscopy data showed that the different techniques have different requirements for signal fluctuation to achieve their optimal performance. While different levels of signal fluctuations had little effect on the SRRF, ESI and SACD images, image reconstructions from both bSOFI and MUSICAL displayed a substantial improvement in their noise rejection, z-sectioning, and overall super-resolution capabilities.

eess.IV↗

arXiv2020

On-chip TIRF nanoscopy by applying Haar wavelet kernel analysis on intensity fluctuations induced by chip illumination

Photonic-chip based TIRF illumination has been used to demonstrate several on-chip optical nanoscopy methods. The sample is illuminated by the evanescent field generated by the electromagnetic wave modes guided inside the optical waveguide. In addition to the photokinetics of the fluorophores, the waveguide modes can be further exploited for introducing controlled intensity fluctuations for exploitation by techniques such as super-resolution optical fluctuation imaging (SOFI). However, the problem of non-uniform illumination pattern generated by the modes contribute to artifacts in the reconstructed image. To alleviate this problem, we propose to perform Haar wavelet kernel (HAWK) analysis on the original image stack prior to the application of (SOFI). HAWK produces a computational image stack with higher spatio-temporal sparsity than the original stack. In the case of multimoded non-uniform illumination patterns, HAWK processing bre aks the mode pattern while introducing spatio-temporal sparsity, thereby differentially affecting the non-uniformity of the illumination. Consequently, this assists nanoscopy methods such as SOFI to better support super-resolution, which is otherwise compromised due to spatial correlation of the mode patterns in the raw image. Furthermore, applying HAWK prior to SOFI alleviates the problem of artifacts due to non-uniform illumination without degrading temporal resolution. Our experimental results demonstrate resolution enhancement as well as reduction in artifacts through the combination of HAWK and SOFI.

physics.optics↗

arXiv2016

Multiple Signal Classification Algorithm for super-resolution fluorescence microscopy

Super-resolution microscopy is providing unprecedented insights into biology by resolving details much below the diffraction limit. State-of-the-art Single Molecule Localization Microscopy (SMLM) techniques for super-resolution are restricted by long acquisition and computational times, or the need of special fluorophores or chemical environments. Here, we propose a novel statistical super-resolution technique of wide-field fluorescence microscopy called MUltiple SIgnal Classification ALgorithm (MUSICAL) which has several advantages over SMLM techniques. MUSICAL provides resolution down to at least 50 nm, has low requirements on number of frames and excitation power and works even at high fluorophore concentrations. Further, it works with any fluorophore that exhibits blinking on the time scale of the recording. We compare imaging results of MUSICAL with SMLM and four contemporary statistical super-resolution methods for experiments of in-vitro actin filaments and datasets provided by independent research groups. Results show comparable or superior performance of MUSICAL. We also demonstrate super-resolution at time scales of 245 ms (using 49 frames at acquisition rate of 200 frames per second) in samples of live-cell microtubules and live-cell actin filaments.

q-bio.QM↗