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Accurate localization of the anatomical landmarks on distal femur bone in the 3D medical images is very important for knee surgery planning and biomechanics analysis. However, the landmark identification process is often conducted manually or by using the inserted auxiliaries, which is time-consuming and lacks of accuracy. In this paper, an automatic localization method is proposed to determine positions...
Shape information is essential in medical image analysis as the anatomical structures usually have strong shape characteristics. Shape priors can resolve ambiguities when the low level appearance is weak or misleading due to imaging artifacts and diseases. In this paper, we propose a shape prior model based on the Gaussian-Bernoulli Restricted Boltzmann Machine (GB-RBM). This powerful generative model...
We propose a semi-Markov model trained in a max-margin learning framework for mitosis event segmentation in large-scale time-lapse phase contrast microscopy image sequences of stem cell populations. Our method consists of three steps. First, we apply a constrained optimization based microscopy image segmentation method that exploits phase contrast optics to extract candidate subsequences in the input...
A method aimed at minimizing image noise while optimizing contrast of image subtle features based on nonsubsampled contourlet transform is presented in this paper. Nonsubsampled contourlet transform, which is a shift-invariant version of the contourlet transform, has better performance in representing image edges than separable wavelet for its anisotropy, directionality and shift-invariance, and is...
A motion panorama is an efficient and compact representation of the underlying video. However, the motion panorama construction process is computationally intensive and hence extremely time consuming. Addressing this issue is crucial when one considers using motion panoramas in a real-time environment such as live video transmission. We present two parallel algorithms for motion panorama construction,...
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