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This paper presents an automated method for actin filament segmentation and tracking for measuring tip elongation rates in total internal reflection fluorescence microscopy (TIRFM) images. The main contributions of the paper are: (i) we use a novel open active contour model for filament segmentation and tracking, which is fast and robust against noise; and (ii) different strategies are proposed to...
In this paper, we introduce a novel algorithm to solve global shape registration problems. We use gray-scale ldquoimagesrdquo to represent source shapes, and propose a novel two-component Gaussian Mixtures (GM) distance map representation for target shapes. Based on this flexible asymmetric image-based representation, a new energy function is defined. It proves to be a more robust shape dissimilarity...
Sparse representation in compressive sensing is gaining increasing attention due to its success in various applications. As we demonstrate in this paper, however, image sparse representation is sensitive to image plane transformations such that existing approaches can not reconstruct the sparse representation of a geometrically transformed image. We introduce a simple technique for obtaining transformation-invariant...
We address the problem of registering a sequence of images in a moving dynamic texture video. This involves optimization with respect to camera motion, the average image, and the dynamic texture model. This problem is highly ill-posed and almost impossible to have good solutions without priors. In this paper, we introduce powerful priors for this problem, based on two simple observations: 1) registration...
Deformable models have had great successes over the past 20 years in medical applications. We have recently developed new classes of deformable models which we term hybrid deformable models to automate the model initialization process and make improvements in segmentation and registration. In this paper we present several hybrid deformable methods we have been developing for segmentation and registration...
We present a novel, variational and statistical approach for shape registration. Shapes of interest are implicitly embedded in a higher-dimensional space of distance transforms. In this implicit embedding space, registration is formulated in a hierarchical manner: the mutual information criterion supports various transformation models and is optimized to perform global registration; then, a B-spline-based...
This paper introduces a novel and efficient algorithm for reconstructing the 3D shapes of tumors from a set of 2D bioluminescence images which are taken by the same camera but after continually rotating the animal by a small angle. The method is efficient and robust enough to be used for analyzing the repeated imaging of a same animal transplanted with gene marked cells. There are several steps in...
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