Krishna Agarwal

• UiT The Arctic University of Norway

Point spread function (PSF) is quite important in modern computational microscopy techniques. Various approaches for measuring and modeling point spread functions have been proposed for both fluorescence and label-free microscopes. Among the various PSF candidates, it is often difficult to evaluate which PSF best suits the microscope and the experi...

Accurate classification of microscopy images is critical for the analysis of biological samples. The availability of large-scale labeled datasets has contributed to recent progress in training large, deep classification models in the medical imaging domain, but methods that cater to a variety of microscopy modalities across a range of biological sa...

We study the online learning problem characterized by the varying input feature space of streaming data. Although LSTMs have been employed to effectively capture the temporal nature of streaming data, they cannot handle the dimension-varying streams in an online learning setting. Therefore, we propose a dynamic LSTM-based novel method, called packe...

Label-free characterization of biological specimens seeks to supplement existing imaging techniques and avoid the need for contrast agents that can disturb the native state of living samples. Conventional label-free optical imaging techniques are compatible with living samples but face challenges such as poor sectioning capability, fragmentary morp...

Cell migration is a fundamental biological process, yet the mechanisms underlying how cells sense and navigate complex environments remain poorly understood. In this study, we developed a system of randomly oriented microgrooves, designed at cellular length scales, to explore motility intelligence in response to varied topographies. These microgroo...

3D cell cultures, including spheroids, have become essential tools in cancer research and drug discovery due to their ability to more accurately mimic in-vivo tissue environments compared to traditional 2D cultures. However, imaging these thick, complex structures remains a challenge, as conventional optical microscopy techniques are limited by sha...

The rising problem of plastic pollution is becoming one of the major environmental issues for the world. In the ocean, plastics undergo degradation into smaller microplastics (MPs) and nanoplastics (NPs). Wild fish and farmed salmon would likely be exposed to these NPs and MPs both through skin and through skin wounds. Keratocyte cells, located in...

Current convolutional neural networks (CNNs) are not designed for large scientific images with rich multi-scale features, such as in satellite and microscopy domain. A new phase of development of CNNs especially designed for large images is awaited. However, application-independent high-quality and challenging datasets needed for such development a...

Hyperspectral quantitative phase microscopy (HS‐QPM) involves the acquisition of phase images across narrow spectral bands, which enables wavelength‐dependent study of different biological samples. In the present work, a compact Linnik‐type HS‐QPM system is developed to reduce the instability and complexity associated with conventional HS‐QPM techn...

Funded by Research Council of Norway

Extracellular matrix diseases like fibrosis are elusive to diagnose early on, to avoid complete loss of organ function or even cancer progression, making early diagnosis crucial. Imaging the matrix densities of proteins like collagen in fixed tissue sections with suitable stains and labels is a standard for diagnosis and staging. However, fine chan...

Funded by UiT The Arctic University of Norway

Structured beams carrying topological defects, namely phase and Stokes singularities, have gained extensive interest in numerous areas of optics. The non-separable spin and orbital angular momentum states of hybridly polarized Stokes singular beams provide additional freedom for manipulating optical fields. However, the characterization of hybridly...

This paper presents data acquired to study the dynamics and interactions of mitochondria and subcellular vesicles in living cardiomyoblasts. The study was motivated by the importance of mitochondrial quality control and turnover in cardiovascular health. Although fluorescence microscopy is an invaluable tool, it presents several limitations. Correl...

Acoustic microscopy is a cutting-edge label-free imaging technology that allows us to see the surface and interior structure of industrial and biological materials. The acoustic image is created by focusing high-frequency acoustic waves on the object and then detecting reflected signals. On the other hand, the quality of the acoustic image's resolu...

We present a gradient light interference microscopy system to visualize 3D quantitative imaging of kidney mesangial cells. We used the system to obtain the morphology of 3D cultured kidney cells of thickness 200 µm.

We propose the idea of phase correlation spectroscopy to investigate the dynamics of diffusion of microparticles in the vicinity of large detection volume utilizing the time-resolved measurements of fluctuations in the phase of the particle.

Conventional methods of assessing sperm quality are based on qualitative analysis of semen. In this paper, we combined time-lapse quantitative phase imaging and deep learning for the classification of healthy and unhealthy sperm cells.

The mesangium is a crucial microenvironment in the kidney. It consists of mesangial cells and extracellular matrix that lends structural integrity to the glomerulus and aids renal filtration. The mesangial cells function in a delicate balance of matrix mechanics and chemical cues to engage in matrix formation, cell interactions, and cytokine produc...

Reconstructing 3D refractive index profile of scatterers using optical microscopy measurements presents several challenges over the conventional microwave and RF domain measurement scenario. These include phaseless and polarization-insensitive measurements, small numerical aperture, as well as a Green’s function where spatial frequencies are integr...

In new chemical environments or for untested combinations of illumination, unexpected changes to the fluorescent labels' photophysical properties, such as photoconversion, can occur. This letter reports on photoblueing of a common cellular probe, LysoTracker Deep Red, in multi-color super-resolution structured illumination microscopy. The dye was f...

Mitochondria are susceptible to damage resulting from their activity as energy providers. Damaged mitochondria can cause harm to the cell and thus mitochondria are subjected to elaborate quality-control mechanisms including elimination via lysosomal degradation in a process termed mitophagy. Basal mitophagy is a house-keeping mechanism fine-tuning...

Fluorescence-based super-resolution optical microscopy (SRM) techniques allow the visualization of biological structures beyond the diffraction limit of conventional microscopes. Despite its successful adoption in cell biology, the integration of SRM into the field of histology has been deferred due to several obstacles. These include limited imagi...

Structured beams carrying topological defects, namely phase and Stokes singularities, have gained extensive interest in numerous areas of optics. The non-separable spin and orbital angular momentum states of hybridly polarized Stokes singular beams provide additional freedom for manipulating optical fields. However, the characterization of hybridly...

The versatile nature of ultrasound imaging finds applications in various fields. A point contact excitation and detection method is generally used for visualizing the acoustic waves in Lead Zirconate Titanate (PZT) ceramics. Such an excitation method with a delta pulse generates a broadband frequency spectrum and wide directional wave vector. The p...

Optical microscopes today have pushed the limits of speed, quality, and observable space in biological specimens revolutionizing how we view life today. Further, specific labeling of samples for imaging has provided insight into how life functions. This enabled label-based microscopy to percolate and integrate into mainstream life science research....

Multispectral quantitative phase imaging (MS-QPI) is a high-contrast label-free technique for morphological imaging of the specimens. The aim of the present study is to extract spectral dependent quantitative information in single-shot using a highly spatially sensitive digital holographic microscope assisted by a deep neural network. There are thr...

A rigorous forward model solver for conventional coherent microscope is presented. The forward model is derived from Maxwell’s equations and models the wave behaviour of light matter interaction. Vectorial waves and multiple-scattering effect are considered in this model. Scattered field can be calculated with given distribution of the refractive i...

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

Scanning acoustic microscopy (SAM) is a non-ionizing and label-free imaging modality used to visualize the surface and internal structures of industrial objects and biological specimens. The image of the sample under investigation is created using high-frequency acoustic waves. The frequency of the excitation signals, the signal-to-noise ratio, and...

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...

Structured illumination microscopy suffers from the need of sophisticated instrumentation and precise calibration. This makes structured illumination microscopes costly and skill-dependent. We present a novel approach to realize super-resolution structured illumination microscopy using an alignment non-critical illumination system and a reconstruct...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...