3,678 research outputs found
Globally Optimal Cell Tracking using Integer Programming
We propose a novel approach to automatically tracking cell populations in
time-lapse images. To account for cell occlusions and overlaps, we introduce a
robust method that generates an over-complete set of competing detection
hypotheses. We then perform detection and tracking simultaneously on these
hypotheses by solving to optimality an integer program with only one type of
flow variables. This eliminates the need for heuristics to handle missed
detections due to occlusions and complex morphology. We demonstrate the
effectiveness of our approach on a range of challenging sequences consisting of
clumped cells and show that it outperforms state-of-the-art techniques.Comment: Engin T\"uretken and Xinchao Wang contributed equally to this wor
Intersubject Regularity in the Intrinsic Shape of Human V1
Previous studies have reported considerable intersubject variability in the three-dimensional geometry of the human primary visual cortex (V1). Here we demonstrate that much of this variability is due to extrinsic geometric features of the cortical folds, and that the intrinsic shape of V1 is similar across individuals. V1 was imaged in ten ex vivo human hemispheres using high-resolution (200 ÎĽm) structural magnetic resonance imaging at high field strength (7 T). Manual tracings of the stria of Gennari were used to construct a surface representation, which was computationally flattened into the plane with minimal metric distortion. The instrinsic shape of V1 was determined from the boundary of the planar representation of the stria. An ellipse provided a simple parametric shape model that was a good approximation to the boundary of flattened V1. The aspect ration of the best-fitting ellipse was found to be consistent across subject, with a mean of 1.85 and standard deviation of 0.12. Optimal rigid alignment of size-normalized V1 produced greater overlap than that achieved by previous studies using different registration methods. A shape analysis of published macaque data indicated that the intrinsic shape of macaque V1 is also stereotyped, and similar to the human V1 shape. Previoud measurements of the functional boundary of V1 in human and macaque are in close agreement with these results
Methods for Analysing Endothelial Cell Shape and Behaviour in Relation to the Focal Nature of Atherosclerosis
The aim of this thesis is to develop automated methods for the analysis of the
spatial patterns, and the functional behaviour of endothelial cells, viewed under
microscopy, with applications to the understanding of atherosclerosis.
Initially, a radial search approach to segmentation was attempted in order to
trace the cell and nuclei boundaries using a maximum likelihood algorithm; it
was found inadequate to detect the weak cell boundaries present in the available
data. A parametric cell shape model was then introduced to fit an equivalent
ellipse to the cell boundary by matching phase-invariant orientation fields of the
image and a candidate cell shape. This approach succeeded on good quality
images, but failed on images with weak cell boundaries. Finally, a support
vector machines based method, relying on a rich set of visual features, and a
small but high quality training dataset, was found to work well on large numbers
of cells even in the presence of strong intensity variations and imaging noise.
Using the segmentation results, several standard shear-stress dependent parameters
of cell morphology were studied, and evidence for similar behaviour
in some cell shape parameters was obtained in in-vivo cells and their nuclei.
Nuclear and cell orientations around immature and mature aortas were broadly
similar, suggesting that the pattern of flow direction near the wall stayed approximately
constant with age. The relation was less strong for the cell and
nuclear length-to-width ratios.
Two novel shape analysis approaches were attempted to find other properties
of cell shape which could be used to annotate or characterise patterns, since a
wide variability in cell and nuclear shapes was observed which did not appear
to fit the standard parameterisations. Although no firm conclusions can yet be
drawn, the work lays the foundation for future studies of cell morphology.
To draw inferences about patterns in the functional response of cells to flow,
which may play a role in the progression of disease, single-cell analysis was performed
using calcium sensitive florescence probes. Calcium transient rates were
found to change with flow, but more importantly, local patterns of synchronisation
in multi-cellular groups were discernable and appear to change with flow.
The patterns suggest a new functional mechanism in flow-mediation of cell-cell
calcium signalling
Nuclei/Cell Detection in Microscopic Skeletal Muscle Fiber Images and Histopathological Brain Tumor Images Using Sparse Optimizations
Nuclei/Cell detection is usually a prerequisite procedure in many computer-aided biomedical image analysis tasks. In this thesis we propose two automatic nuclei/cell detection frameworks. One is for nuclei detection in skeletal muscle fiber images and the other is for brain tumor histopathological images.
For skeletal muscle fiber images, the major challenges include: i) shape and size variations of the nuclei, ii) overlapping nuclear clumps, and iii) a series of z-stack images with out-of-focus regions. We propose a novel automatic detection algorithm consisting of the following components: 1) The original z-stack images are first converted into one all-in-focus image. 2) A sufficient number of hypothetical ellipses are then generated for each nuclei contour. 3) Next, a set of representative training samples and discriminative features are selected by a two-stage sparse model. 4) A classifier is trained using the refined training data. 5) Final nuclei detection is obtained by mean-shift clustering based on inner distance. The proposed method was tested on a set of images containing over 1500 nuclei. The results outperform the current state-of-the-art approaches.
For brain tumor histopathological images, the major challenges are to handle significant variations in cell appearance and to split touching cells. The proposed novel automatic cell detection consists of: 1) Sparse reconstruction for splitting touching cells. 2) Adaptive dictionary learning for handling cell appearance variations. The proposed method was extensively tested on a data set with over 2000 cells. The result outperforms other state-of-the-art algorithms with F1 score = 0.96
Localization of protein aggregation in Escherichia coli is governed by diffusion and nucleoid macromolecular crowding effect
Aggregates of misfolded proteins are a hallmark of many age-related diseases.
Recently, they have been linked to aging of Escherichia coli (E. coli) where
protein aggregates accumulate at the old pole region of the aging bacterium.
Because of the potential of E. coli as a model organism, elucidating aging and
protein aggregation in this bacterium may pave the way to significant advances
in our global understanding of aging. A first obstacle along this path is to
decipher the mechanisms by which protein aggregates are targeted to specific
intercellular locations. Here, using an integrated approach based on
individual-based modeling, time-lapse fluorescence microscopy and automated
image analysis, we show that the movement of aging-related protein aggregates
in E. coli is purely diffusive (Brownian). Using single-particle tracking of
protein aggregates in live E. coli cells, we estimated the average size and
diffusion constant of the aggregates. Our results evidence that the aggregates
passively diffuse within the cell, with diffusion constants that depend on
their size in agreement with the Stokes-Einstein law. However, the aggregate
displacements along the cell long axis are confined to a region that roughly
corresponds to the nucleoid-free space in the cell pole, thus confirming the
importance of increased macromolecular crowding in the nucleoids. We thus used
3d individual-based modeling to show that these three ingredients (diffusion,
aggregation and diffusion hindrance in the nucleoids) are sufficient and
necessary to reproduce the available experimental data on aggregate
localization in the cells. Taken together, our results strongly support the
hypothesis that the localization of aging-related protein aggregates in the
poles of E. coli results from the coupling of passive diffusion- aggregation
with spatially non-homogeneous macromolecular crowding. They further support
the importance of "soft" intracellular structuring (based on macromolecular
crowding) in diffusion-based protein localization in E. coli.Comment: PLoS Computational Biology (2013
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