40,694 research outputs found
Particle detection and tracking in fluorescence time-lapse imaging: a contrario approach
This paper proposes a probabilistic approach for the detection and the
tracking of particles in fluorescent time-lapse imaging. In the presence of a
very noised and poor-quality data, particles and trajectories can be
characterized by an a contrario model, that estimates the probability of
observing the structures of interest in random data. This approach, first
introduced in the modeling of human visual perception and then successfully
applied in many image processing tasks, leads to algorithms that neither
require a previous learning stage, nor a tedious parameter tuning and are very
robust to noise. Comparative evaluations against a well-established baseline
show that the proposed approach outperforms the state of the art.Comment: Published in Journal of Machine Vision and Application
Efficient Algorithms for Moral Lineage Tracing
Lineage tracing, the joint segmentation and tracking of living cells as they
move and divide in a sequence of light microscopy images, is a challenging
task. Jug et al. have proposed a mathematical abstraction of this task, the
moral lineage tracing problem (MLTP), whose feasible solutions define both a
segmentation of every image and a lineage forest of cells. Their branch-and-cut
algorithm, however, is prone to many cuts and slow convergence for large
instances. To address this problem, we make three contributions: (i) we devise
the first efficient primal feasible local search algorithms for the MLTP, (ii)
we improve the branch-and-cut algorithm by separating tighter cutting planes
and by incorporating our primal algorithms, (iii) we show in experiments that
our algorithms find accurate solutions on the problem instances of Jug et al.
and scale to larger instances, leveraging moral lineage tracing to practical
significance.Comment: Accepted at ICCV 201
Exploiting flow dynamics for super-resolution in contrast-enhanced ultrasound
Ultrasound localization microscopy offers new radiation-free diagnostic tools
for vascular imaging deep within the tissue. Sequential localization of echoes
returned from inert microbubbles with low-concentration within the bloodstream
reveal the vasculature with capillary resolution. Despite its high spatial
resolution, low microbubble concentrations dictate the acquisition of tens of
thousands of images, over the course of several seconds to tens of seconds, to
produce a single super-resolved image. %since each echo is required to be well
separated from adjacent microbubbles. Such long acquisition times and stringent
constraints on microbubble concentration are undesirable in many clinical
scenarios. To address these restrictions, sparsity-based approaches have
recently been developed. These methods reduce the total acquisition time
dramatically, while maintaining good spatial resolution in settings with
considerable microbubble overlap. %Yet, non of the reported methods exploit the
fact that microbubbles actually flow within the bloodstream. % to improve
recovery. Here, we further improve sparsity-based super-resolution ultrasound
imaging by exploiting the inherent flow of microbubbles and utilize their
motion kinematics. While doing so, we also provide quantitative measurements of
microbubble velocities. Our method relies on simultaneous tracking and
super-localization of individual microbubbles in a frame-by-frame manner, and
as such, may be suitable for real-time implementation. We demonstrate the
effectiveness of the proposed approach on both simulations and {\it in-vivo}
contrast enhanced human prostate scans, acquired with a clinically approved
scanner.Comment: 11 pages, 9 figure
A statistical analysis of particle trajectories in living cells
Recent advances in molecular biology and fluorescence microscopy imaging have
made possible the inference of the dynamics of single molecules in living
cells. Such inference allows to determine the organization and function of the
cell. The trajectories of particles in the cells, computed with tracking
algorithms, can be modelled with diffusion processes. Three types of diffusion
are considered : (i) free diffusion; (ii) subdiffusion or (iii) superdiffusion.
The Mean Square Displacement (MSD) is generally used to determine the different
types of dynamics of the particles in living cells (Qian, Sheetz and Elson
1991). We propose here a non-parametric three-decision test as an alternative
to the MSD method. The rejection of the null hypothesis -- free diffusion -- is
accompanied by claims of the direction of the alternative (subdiffusion or a
superdiffusion). We study the asymptotic behaviour of the test statistic under
the null hypothesis, and under parametric alternatives which are currently
considered in the biophysics literature, (Monnier et al,2012) for example. In
addition, we adapt the procedure of Benjamini and Hochberg (2000) to fit with
the three-decision test setting, in order to apply the test procedure to a
collection of independent trajectories. The performance of our procedure is
much better than the MSD method as confirmed by Monte Carlo experiments. The
method is demonstrated on real data sets corresponding to protein dynamics
observed in fluorescence microscopy.Comment: Revised introduction. A clearer and shorter description of the model
(section 2
Fluorescent and photo-oxidizing TimeSTAMP tags track protein fates in light and electron microscopy.
Protein synthesis is highly regulated throughout nervous system development, plasticity and regeneration. However, tracking the distributions of specific new protein species has not been possible in living neurons or at the ultrastructural level. Previously we created TimeSTAMP epitope tags, drug-controlled tags for immunohistochemical detection of specific new proteins synthesized at defined times. Here we extend TimeSTAMP to label new protein copies by fluorescence or photo-oxidation. Live microscopy of a fluorescent TimeSTAMP tag reveals that copies of the synaptic protein PSD95 are synthesized in response to local activation of growth factor and neurotransmitter receptors, and preferentially localize to stimulated synapses in rat neurons. Electron microscopy of a photo-oxidizing TimeSTAMP tag reveals new PSD95 at developing dendritic structures of immature neurons and at synapses in differentiated neurons. These results demonstrate the versatility of the TimeSTAMP approach for visualizing newly synthesized proteins in neurons
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