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In this paper, we present a new fully automatic approach for noise parameter estimation in the context of fluorescence imaging systems. In particular, we address the problem of Poisson-Gaussian noise modeling in the nonstationary case. In microscopy practice, the nonstationarity is due to the photobleaching effect. The proposed method consists of an adequate moment based initialization followed by...
A fully automated 3D Stitching tool designed for the very the large images produced by a special class of microscopes capable to acquire volumes of about 1 cm3 at micrometric resolution is presented. Exploiting some unique characteristics of the acquired images the tool makes it possible the accurate reconstruction of images of 1 TB or more in a reasonable time, even on workstations with limited resources...
This paper presents a computational approach for detection of filamentous networks in 3D tomographic electron microscopy. Due to the general heterogeneity of chemical staining, imaged signatures may appear punctate and discontinuous. Very often, there is a necessity to characterize organization and phenotypic signatures of stained structures. This is the example of polysaccharides in the plant cell...
Polarisation of light affords the means to perform robust orientational measurements of single molecules and sub-wavelength asymmetric scatterers. The precision with which such measurements can be made can be quantified using Fisher information and the Cramér-Rao lower bound. Specifically, a fundamental limit of 0.5/N radians (on average) is found where N is the number of detected photons. Measurement...
The study of cellular processes in three-dimensions is severely limited by the lack of imaging methodologies that allow for fast 3D tracking of cellular events and 3D superresolution imaging of sub-cellular structures. We have developed a 3D imaging modality, multifocal plane microscopy (MUM), that provides a powerful approach for 3D single molecule tracking and 3D superresolution microscopy. Here...
We propose a robust statistical framework for correcting the movements of vesicles in frequency domain FLIM imaging. Movement and lifetime are jointly estimated in a three-step procedure. Robust M-estimators are mainly used to improve accuracy in temporally-varying noisy images. The performance of the proposed method is demonstrated on both simulated and real samples.
Single-particle tracking is computationally a challenging problem, and usually solved with local methods. Local methods suffer from defects in the image data or in the detection of particles, such as temporal disappearing of particles. A particle tracking method has to provide a solution also to real disappearing and appearing of particles as a result of merging and splitting. Here, we present an...
Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a two-step multi-frame association finding algorithm which is based on a temporally semi-global formulation as well as combines a spatially global and a spatially local approach. Using this multi-frame association finding algorithm...
Recent work has revealed that, contrary to expectations, the protein machineries responsible for regulating cellular polarity in fission yeast cells localises cortically to the semi-spherical tips of each cell as punctual structures. To quantify this discovery and try and reconcile it with previous findings, a statistical co-localisation framework is set up. We use spatial statistics to analyse collections...
The random walker method [1] has many nice characteristics for 3D image segmentation. However, it is computational expensive and slow due to a massive linear system to be solved. In this work, we take advantage of the probabilistic output from the random walker method applied to a small downsampled image. By using the original image and seeds information, a novel edge-preserving method is introduced...
Recently, the in vivo imaging of pulmonary alveoli was made possible thanks to confocal microscopy. For these new images, we wish to aid the clinician by developing a computer-aided diagnosis system, able to detect a pathological state in these images. An original approach that combines a texture-based characterization of the images and uses a boosted cascade of classifiers to detect a pathological...
Three-dimensional (3D) structure determination by single-particle analysis of cryo-electron microscopy (cryo-EM) images requires many parameters to be determined from extremely noisy data. This makes the method prone to overfitting, that is, when structures describe noise rather than signal, in particular near their resolution limit where noise levels are highest. Cryo-EM structures are typically...
We present a fast and robust approach to tracking whole fluorescent cells in time-lapse series. The proposed tracking scheme involves two steps. First, coherence-enhancing diffusion filtering is applied on each frame to reduce the amount of noise and enhance flow-like structures. Second, the enhanced cell boundaries are detected by minimizing the Chan-Vese model in a fast level set-like framework...
The presentation gives an introduction and overview of our recently developed Stochastic Optical Fluctuation Imaging microscopy technique. The theoretical foundations are given and the method is exemplified on several model systems. Its advantages and limitations are discussed, and many applications of SOFI in cell microscopy are presented.
We present a new fast active contour for images in 3D microscopy. We introduce a fully parametric design that relies on exponential B-spline bases and allows us to impose a sphere-like topology. The proposed 3D snake can approximate blob-like objects with good accuracy. The optimization process is remarkably fast. Our technique yields successful segmentation results even for a challenging data set...
The analysis of time lapse data becomes a more and more important tool in (stem) cell biology, as this method enables a marker free analysis of cell populations over time and allows for the reconstruction of genealogical trees; these information can help to understand the mechanisms behind cell proliferation and differentiation. However, the crucial steps in a cell tracking algorithm (cell segmentation,...
In this article, we are interested in restoring images from 3D fluorescence microscopy. In fact, these images are affected by a depth-variant blur due to light refraction phenomenon. We present and compare two different restoration strategies for that problem. The first one is based on multiple deconvolutions with depth-invariant blur functions and the second one consists in using a depth-variant...
The application of multi-tag protocols in fluorescence microscopy allows the visualization of a large number (> 10) of molecules (i. e. proteins) in a sample (like a tissue section). However, the analysis of such high dimensional bioimages is a difficult task for most of the labs, since software solutions for particular data mining steps are difficult to use or just not available. In this paper...
We propose to use a kernel intensity penalizer (KIP) in the blind maximum likelihood expectation maximization (MLEM) deconvolution scheme. With this very general kernel regularization term, we can stabilize the blind MLEM scheme even for the deconvolution of wide-field microscopic recordings. No complex prior point spread function models are needed. We combine state of the art optimization schemes...
The understanding of the embryogenesis in living systems requires reliable quantitative analysis of the cell migration throughout all the stages of development. This is a major challenge of the ”in-toto” reconstruction based on different modalities of ”in-vivo” imaging techniques-spatio-temporal resolution and image artifacts and noise. Several methods for cell tracking are available, but expensive...
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