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Highly efficient and scalable framework for high-speed super-resolution microscopy
(Journal article; Tidsskriftartikkel; Peer reviewed, 2021-07-05)
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 improving its low computational performance. We first ...
Artefact removal in ground truth deficient fluctuations-based nanoscopy images using deep learning
(Journal article; Tidsskriftartikkel; Peer reviewed, 2020-12-08)
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 statistical analysis techniques. Due to several physical ...
Object detection neural network improves Fourier ptychography reconstruction
(Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-23)
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 is Fourier ptychography. This microscopy technique ...
Learning Nanoscale Motion Patterns of Vesicles in Living Cells
(Conference object; Konferansebidrag, 2020-08-05)
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 for this problem. We propose an integrative approach, built upon physics based simulations, nanoscopy algorithms, and shallow ...
Silicon substrate significantly alters dipole-dipole resolution in coherent microscope
(Journal article; Tidsskriftartikkel; Peer reviewed, 2020-12-16)
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 substrate. Numerical analysis are performed in order ...
Blind Super-Resolution Approach for Exploiting Illumination Variety in Optical-Lattice Illumination Microscopy
(Journal article; Tidsskriftartikkel; Peer reviewed, 2021-08-19)
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. Here, we present an alternate blind reconstruction ...
Multimodal on-chip nanoscopy and quantitative phase imaging reveals the nanoscale morphology of liver sinusoidal endothelial cells
(Journal article; Tidsskriftartikkel; Peer reviewed, 2021-11-23)
Visualization of three-dimensional (3D) morphological changes in the subcellular structures of a biological specimen is a major challenge in life science. Here, we present an integrated chip-based optical nanoscopy combined with quantitative phase microscopy (QPM) to obtain 3D morphology of liver sinusoidal endothelial cells (LSEC). LSEC have unique morphology with small nanopores (50-300 nm in ...
Physics-based machine learning for subcellular segmentation in living cells
(Journal article; Tidsskriftartikkel; Peer reviewed, 2021-12-15)
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. Unsupervised segmentation
approaches are quite ...
Photonic-chip: a multimodal imaging tool for histopathology
(Conference object; Konferansebidrag, 2021-04)
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.
Label-free imaging on waveguide platform with enhanced resolution and contrast
(Conference object; Konferansebidrag, 2021)
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 have random spatial distributions within the integration ...