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We present an energy-minimization-based framework for locating the centerline and estimating the width of tubelike objects from their structural network with a nonparametric model. The nonparametric representation promotes simple modeling of nested branches and -way furcations, i.e., structures that abound in an arterial network, e.g., a cerebrovascular circulation. Our method is capable of extracting...
Non-rigid image registration is widely used in medical image analysis and processing. We recently proposed a novel learning-based similarity measure for non-rigid image registration. The novel similarity measure is constructed by using two Kullback-Leibler distances (KLD), which are based on the a priori knowledge of the joint intensity distribution of a pre-aligned image pair. In this paper, we propose...
Multi-modal image registration is a momentous technology in medical image processing and analysis. In order to improve the robustness and accuracy of multi-modal rigid image registration, a novel learning-based dissimilarity function is proposed in this paper. This novel dissimilarity function is based on measuring the dissimilarity between the joint intensity distribution of the testing image pair...
Multi-modal non-rigid image registration is widely used in different areas, including medical image analysis and image processing. In this paper, we introduce a new learning-based method for non-rigid image registration. The proposed method is based on a priori knowledge of the joint intensity distribution of a pre-aligned image pair. The similarity and dissimilarity of the expected and observed joint...
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