Krishna Agarwal

UiT The Arctic University of Norway

Fluorescence microscopy is a quintessential tool for observing cells and understanding the underlying mechanisms of life-sustaining processes of all living organisms. The problem of extracting 3D shape of mitochondria from fluorescence microscopy images remains unsolved due to the complex and varied shapes expressed by mitochondria and the poor res...

Mitochondria play a crucial role in cellular metabolism. This paper presents a novel method to visualize mitochondria in living cells without the use of fluorescent markers. We propose a physics-guided deep learning approach for obtaining virtually labeled micrographs of mitochondria from bright-field images. We integrate a microscope’s point sprea...

The article elucidates the physical mechanism behind the generation of superior-contrast and high-resolution label-free images using an optical waveguide. Imaging is realized by employing a high index contrast multi-moded waveguide as a partially coherent light source. The modes provide near-field illumination of unlabeled samples, thereby repositi...

Multiple signal classification algorithm (MUSICAL) provides a super-resolution microscopy method. In the previous research, MUSICAL has enabled data-parallelism well on a desktop computer or a Linux-based server. However, the running time needs to be shorter. This paper will develop a new parallel MUSICAL with high efficiency and scalability on a c...

Intact skin is of uttermost importance for fish welfare. The fish skin provides an environmental barrier and protects against invading pathogens. However, both pathogens and physical insults cause skin wounds that are of major concern in modern fish farming. The behavior and interactions between keratocyte cells and sheets of cells are not well und...

Acoustic microscopy is a cutting-edge label-free imaging technique to visualize surface and internal structure of industrial and biological specimens. Focusing high-frequency acoustic waves to the object followed by detection of echo signals results in the final acoustic image. However, resolution of the acoustic image depends on the signal to nois...

This three-dimensional structured illumination microscopy (3DSIM) dataset was generated to highlight the suitability of 3DSIM to investigate mitochondria-derived vesicles (MDVs) in H9c2 cardiomyoblasts in living or fixed cells. MDVs act as a mitochondria quality control mechanism. The cells were stably expressing the tandem-tag eGFP-mCherry-OMP25-T...

Histology involves the observation of structural features in tissues using a microscope. While diffraction-limited optical microscopes are commonly used in histological investigations, their resolving capabilities are insufficient to visualize details at subcellular level. Although a novel set of super-resolution optical microscopy techniques can f...

Multi-spectral quantitative phase imaging (MS-QPI) is a cutting-edge label-free technique to determine the morphological changes, refractive index variations and spectroscopic information of the specimens. The bottleneck to implement this technique to extract quantitative information, is the need of more than two measurements for generating MS-QPI...

Solving electromagnetic inverse scattering problems (ISPs) is challenging due to the intrinsic nonlinearity, ill-posedness, and expensive computational cost. Recently, deep neural network (DNN) techniques have been successfully applied on ISPs and shown potential of superior imaging over conventional methods. In this paper, we discuss techniques fo...

Optical waveguide chips are shown as an alternative to far-field optics for the excitation of biological microscopy samples, with high refractive index materials and photonic circuits pushing the boundaries of conventional super-resolution optical microscopy implementations.

We present a highly spatially sensitive quantitative phase microscopy system integrated with on-chip nanoscopy to visualize 3D morphology of liver sinusoidal endothelial cells (LSECs). We used the system to obtain 3D morphology of LSEC by using chip-based nanoscopy for lateral super-resolution, and QPM for mapping nanoscale thickness.

Segmenting subcellular structures in living cells from fluorescence microscope images is a ground truth (GT)-deficient problem. The microscopes’ three-dimensional blurring function, finite optical resolution due to light diffraction, finite pixel resolution and the complex morphological manifestations of the structures all contribute to GT-hardness...

Significance We propose the integration of chip-based optical nanoscopy with high spatially sensitive quantitative phase microscopy to obtain three-dimensional (3D) morphology of liver sinusoidal endothelial cells (LSEC). LSEC contain large numbers of transcellular nanopores —“fenestrations”—in the plasma membrane, typically clustered in groups of...

Solving electromagnetic inverse scattering problems (ISPs) is challenging due to the intrinsic nonlinearity, ill-posedness, and expensive computational cost. Recently, deep neural network (DNN) techniques have been successfully applied on ISPs and shown potential of superior imaging over conventional methods. In this paper, we analyse the analogy b...

Mitochondria are essential energy-providing organelles of particular importance in energy-demanding tissue such as the heart. The production of mitochondria-derived vesicles (MDVs) is a cellular mechanism by which cells ensure a healthy pool of mitochondria. These vesicles are small and fast-moving objects not easily captured by imaging. In this wo...

Acoustic microscopy has found various applications from nondestructive testing (NDT) to medical imaging for quantitative information. Scanning acoustic microscope (SAM) used for imaging and sample preparation have significant bearing on the conclusions drawn. In most cases while scanning the sample, there appear lots of artifacts due to the presenc...

Contrast in fluorescence microscopy images allows for the differentiation between different structures by their difference in intensities. However, factors such as point-spread function and noise may reduce it, affecting its interpretability. We identified that fluctuation of emitters in a stack of images can be exploited to achieve increased contr...

Chip-based Evanescent Light Scattering (cELS) utilizes the multiple modes of a high-index contrast optical waveguide for near-field illumination of unlabeled samples, thereby repositioning the highest spatial frequencies of the sample into the far-field. The multiple modes scattering off the sample with different phase differences is engineered to...

Optical-lattice illumination patterns help in pushing high spatial frequency components of the sample into the optical transfer function of a collection microscope. However, exploiting these high-frequency components require precise knowledge of illumination if reconstruction approaches similar to structured illumination microscopy are employed. He...

The multiple signal classification algorithm (MUSICAL) is a statistical super-resolution technique for wide-field fluorescence microscopy. Although MUSICAL has several advantages, such as its high resolution, its low computational performance has limited its exploitation. This paper aims to analyze the performance and scalability of MUSICAL for imp...

Photonic chip-based total internal reflection fluorescence microscopy (c-TIRFM) is an emerging technology enabling a large TIRF excitation area decoupled from the detection objective. Additionally, due to the inherent multimodal nature of wide waveguides, it is a convenient platform for introducing temporal fluctuations in the illumination pattern....

Histopathological assessment involves the identification of anatomical variations in tissues that are associated with diseases. While diffraction-limited optical microscopes assist in the diagnosis of a wide variety of pathologies, their resolving capabilities are insufficient to visualize some anomalies at subcellular level. Although a novel set o...

Histopathological assessment involves the identification of anatomical variations in tissues that are associated with diseases. While diffraction-limited optical microscopes assist in the diagnosis of a wide variety of pathologies, their resolving capabilities are insufficient to visualize some anomalies at subcellular level. Although a novel set o...

Examining specific sub-cellular structures while minimizing cell perturbation is important in the life sciences. Fluorescence labeling and imaging is widely used for introducing specificity despite its perturbative and photo-toxic nature. With the advancement of deep learning, digital staining routines for label-free analysis have emerged as a repl...

Image denoising or artefact removal using deep learning is possible in the availability of supervised training dataset acquired in real experiments or synthesized using known noise models. Neither of the conditions can be fulfilled for nanoscopy (super-resolution optical microscopy) images that are generated from microscopy videos through statistic...

We propose the photonic-chip as a multimodal imaging platform for histopathological assessment, allowing large fields-of-view across diverse microscopy methods including total internal reflection fluorescence and single-molecule localization.

Considering a coherent microscopy setup, influences of the substrate below the sample in the imaging performances are studied, with a focus on high refractive index substrate such as silicon. Analytical expression of 3D full-wave vectorial point spread function, i.e. the dyadic Green’s function is derived for the optical setup together with the sub...

High resolution microscopy is heavily dependent on superb optical elements and superresolution microscopy even more so. Correcting unavoidable optical aberrations during post-processing is an elegant method to reduce the optical system's complexity. A prime method that promises superresolution, aberration correction, and quantitative phase imaging...

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 introd...

Multiple signal classification algorithm (MUSICAL) exploits temporal fluctuations in fluorescence intensity to perform super-resolution microscopy by computing the value of a super-resolving indicator function across a fine sample grid. A key step in the algorithm is the separation of the measurements into signal and noise subspaces, based on a sin...

Fibrosis is an extracellular matrix disease affecting several vital organs' functions and can lead to life-threatening pathologies like cancer. The standard diagnostic protocol involves an immuno-histochemical examination of the fibrosis-linked protein's distribution in the tissues. Of specific interest are the primarily affected dense matrix-prote...

Image denoising or artefact removal using deep learning is possible in the availability of supervised training dataset acquired in real experiments or synthesized using known noise models. Neither of the conditions can be fulfilled for nanoscopy (super-resolution optical microscopy) images that are generated from microscopy videos through statistic...

Multiple signal classification algorithm (MUSICAL) exploits temporal fluctuations in fluorescence intensity to perform super-resolution microscopy by computing the value of a super-resolving indicator function across a fine sample grid. A key step in the algorithm is the separation of the measurements into signal and noise subspaces, based on a sin...

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...

Streaming classification methods assume the number of input features is fixed and always received. But in many real-world scenarios demand is some input features are reliable while others are unreliable or inconsistent. In this paper, we propose a novel deep learning-based model called Auxiliary Network (Aux-Net), which is scalable and agile. It em...

In many real-world scientific problems, generating ground truth (GT) for supervised learning is almost impossible. The causes include limitations imposed by scientific instrument, physical phenomenon itself, or the complexity of modeling. Performing artificial intelligence (AI) tasks such as segmentation, tracking, and analytics of small sub-cellul...

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...

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 introd...

At high microwave frequencies, phase measurement is difficult to meet the accuracy required for imaging, and it is more susceptible to noise pollution. Consequently, it is important to develop inversion models and algorithms for electromagnetic inverse scattering problems with phaseless data (PD-ISPs). Compared to the ISPs with full data (FD-ISPs),...

Detecting and analyzing nanoscale motion patterns of vesicles, smaller than the microscope resolution (∼ 250 nm), inside living biological cells is a challenging problem. State-of-the-art CV approaches based on detection, tracking, optical flow or deep learning perform poorly on this problem. We propose an integrative approach built upon physics-ba...

We present an open-source implementation of the fluctuation-based nanoscopy method MUSICAL for ImageJ. This implementation improves the algorithm’s computational efficiency and takes advantage of multi-threading to provide orders of magnitude faster reconstructions than the original MATLAB implementation. In addition, the plugin is capable of gener...

The application of artificial intelligence (AI) is relatively new in microscopy. Advances in microscopes and AI are greatly expanding the possibilities for microscopy image analysis and interpretation, which is of special importance to researchers in biology. It has been noted earlier that the state-of-the-art AI methods generally perform poorly du...

Various natural and artificial materials are anisotropic. The inverse scattering problem of anisotropic scatterers is widely involved in oil detection, nondestructive evaluation of composite materials and microscopic imaging of biological tissue. In this contribution, the two-dimensional inverse scattering problem of biaxial anisotropic scatterers...

The application of piezoelectric materials, such as Lead Zirconate Titanate (ZrxTi1-x) O3 (PZT) is increasing in multiple dynamic industries such as structural health monitoring, wireless energy harvesting devices, measuring blood flow, etc.The main aim of this paper is to denoise the images generated by dual point excitation and detection method f...

A complete study of electric field vectors and efficiencies of diffraction orders for a phase pattern addressed to a pixelated spatial light modulator (SLM) is discussed here. General mathematical expressions of electric field vectors from SLM are explored here analytically for an arbitrary pattern on SLM with a given input electric field. Using th...

Ultrasound based structural health monitoring of piezoelectric material is challenging if a damage changes at a microscale over time. Classifying geometrically similar damages with a difference in diameter as small as 100 μ m is difficult using conventional sensing and signal analysis approaches. Here, we use an unconventional ultrasound sensing ap...

Localization microscopy and multiple signal classification algorithm use temporal stack of image frames of sparse emissions from fluorophores to provide super-resolution images. Localization microscopy localizes emissions in each image independently and later collates the localizations in all the frames, giving same weight to each frame irrespectiv...

This paper presents eigen-analysis of image stack of blinking fluorophores to identify the components that enable super-resolved imaging of blinking fluorophores. Eigen-analysis reveals that the contributions of spatial distribution of fluorophores and their temporal photon emission characteristics can be completely separated. While cross-emitter c...

Supplementary Figures, Supplementary Tables, Supplementary Notes, Supplementary Methods and Supplementary References.

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....

A quantitative approach is used to determine an effective height of probe beyond which the capacitance contribution is not significant in microwave impedance microscopy (MIM). We compare the effective height for three different modes of measurement, i.e., capacitance C(l) (l is the tip-sample distance), derivative of capacitance (C′(l)), and second...

Medical and biological signals span almost the entire spectrum from EEG to X-rays and their sources range from molecular scales to large organs such as heart, brain, and muscles. Signal processing techniques (including image analysis) are constantly serving towards improving the state-of-the-art in medical and biological data analysis and interpret...

We propose a method for classifying radiometric oceanic color data measured by hyperspectral satellite sensors into known spectral classes, irrespective of the downwelling irradiance of the particular day, i.e., the illumination conditions. The focus is not on retrieving the inherent optical properties but to classify the pixels according to the kn...

An innovative methodology is proposed to solve quantitative three-dimensional microwave imaging problems formulated within the contrast source framework. The introduced technique is based on the combination of an efficient iterative multiscaling strategy aimed at mitigating local minimum issue arising in inverse scattering problems, and a local sea...

This paper discusses the problem of detecting wearable RF devices used in elderly care. Events such as blood sugar level drop, or physical fall of the elderly person, are stochastic events and are digitally recorded and/or broadcast to a monitoring system through home. The stochastic nature of the events and independence of the digital broadcast fo...

We present a detailed analysis of tip-sample interaction in microwave impedance microscopy by applying lumped element method in this paper. A lumped element model is proposed and the value for each lumped element component is optimized. We find that reflection coefficient including both magnitude and phase obtained by simulation using this model ma...

This paper discusses the problem of choosing an appropriate direction of the test dipole used in linear sampling for the 2-dimensional inverse scattering problem of the transverse electric case. In particular, we propose two approaches, one purely mathematical and the other based on the physics theory of multipole expansion of the scattered magneti...

Solving by finite differences for the magnetic field in an E-polarization induction problem is an unorthodox approach because it is simpler to obtain the solution for the single component of the electric field, from which the two magnetic components are readily found by differentiation. Nevertheless, when the E-polarization model appears as the 2-D...

Two popular methods for obtaining a preliminary 1-D geo-electric model from magnetotelluric data are the simple inversion algorithms due to Niblett, Bostick or Schmucker, and the modelling scheme of Fischer & LeQuang. the former provides resistivity values at different depths, while the latter uses an optimizing program to obtain the resistivities...

SUMMARY We examine the relationship between the seven invari- ants of the complex MT tensor, which we previously proposed as a vehicle for testing the dimensionality of the regional conductivity structure prior to an analysis of MT data, and the three invariants of the real 'phase tensor', recently introduced as an innovative aid in the treatment o...

The magnetotelluric impedance tensor is defined in terms of seven independent parameters that are invariant under a rotation of the horizontal axes on the surface of the Earth, plus an angle that defines the orientation of the axes of reference. The invariants are algebraically related to but nevertheless different from those recently proposed by S...

Decomposition of the magnetotelluric (MT) tensor when the electric field alone is subject to local galvanic distortion has received much attention in recent years. Recently some authors have extended such procedures to include the effects of the associated magnetic field distortion as well. With the aid of a three-dimensional modelling program the...

Dr. P. F. Chen (hereafter PFC) has questioned two main differences between the CDK analogue model and his FDM numerical results: 1) The CDK analogue model in-phase Vy fall off rapidly with increasing period, whereas his numeri- cal Hz/Hy do not; 2) The CDK quadrature Vy do not show a reversal, whereas his Hz/Hy do. Upon examining the curves in Fig....