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We apply a recently developed framework for analyzing the convergence of stochastic algorithms to the general problem of large-scale nonconvex composite optimization more generally, and nonconvex likelihood maximization in particular. Our…
Deep learning algorithms offer a powerful means to automatically analyze the content of medical images. However, many biological samples of interest are primarily transparent to visible light and contain features that are difficult to…
Recent developments in image acquisition literature have miniaturized the confocal laser endomicroscopes to improve usability and flexibility of the apparatus in actual clinical settings. However, miniaturized devices collect less light and…
If supersymmetric particles are produced at the Large Hadron Collider it becomes very important not only to identify them, but also to determine their masses with the highest possible precision, since this may lead to an understanding of…
Particle tracking is common in many biophysical, ecological, and micro-fluidic applications. Reliable tracking information is heavily dependent on of the system under study and algorithms that correctly determines particle position between…
Stacks of digital astronomical images are combined in order to increase image depth. The variable seeing conditions, sky background and transparency of ground-based observations make the coaddition process non-trivial. We present image…
Correlative microscopy aims at combining two or more modalities to gain more information than the one provided by one modality on the same biological structure. Registration is needed at different steps of correlative microscopies…
We present an algorithm for performing precise aperture photometry on critically sampled astrophysical images. The method is intended to overcome the small-aperture limitations imposed by point-sampling. Aperture fluxes are numerically…
The full understanding of cellular functions requires information about protein numbers for various biomolecular assemblies and their dynamics, which can be partly accessed by super-resolution fluorescence microscopy. Yet, many protein…
Accurately measuring the translations of objects between images is essential in many fields, including biology, medicine, chemistry, and physics. One important application is tracking one or more particles by measuring their apparent…
Confocal microscopy is the backbone of cellular research labs across the world but unfortunately, the imaging is restricted to a single plane. Chromatic confocal microscopy offers the possibility to image multiple planes simultaneously thus…
We present novel methods to perform plenoptic imaging at the diffraction limit by measuring intensity correlations of light. The first method is oriented towards plenoptic microscopy, a promising technique which allows refocusing and…
We construct optimal measurements, achieving the ultimate precision predicted by quantum theory, for the simultaneous estimation of centroid, separation, and relative intensities of two incoherent point sources using a linear optical…
Images of semiconductor `dot in rods' and their small clusters are studied by measuring the second-order correlation function with a spatially resolving ICCD camera. This measurement allows one to distinguish between a single dot and a…
Exoplanetary science is a very active field of astronomy nowadays, with questions still opened such as how planetary systems form and evolve (occurrence, process), why such a diversity of exoplanets is observed (mass, radius, orbital…
Defects in crystalline materials control the properties of materials, and their characterization focuses our strategies to optimize performance. Electron microscopy has served as the backbone of our understanding of defect structure and…
Automatic detection and segmentation of cells and nuclei in microscopy images is important for many biological applications. Recent successful learning-based approaches include per-pixel cell segmentation with subsequent pixel grouping, or…
The ability to track a moving vehicle is of crucial importance in numerous applications. The task has often been approached by the importance sampling technique of particle filters due to its ability to model non-linear and non-Gaussian…
Optical absorption imaging has become a common technique for detecting the density distribution of ultracold atoms. The defocus effect generally produces artificial spatial structures in the obtained images, which confuses our understanding…
Cluster-scale strong lensing is a powerful tool for exploring the properties of dark matter and constraining cosmological models. However, due to the complex parameter space, pixelized strong lens modeling in galaxy clusters is…