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In order to reduce artifacts in match metric and improve the registration speed in medical image registration, three types of improved nearest neighbor (NN) interpolators based on confidence region (CR) are studied. These improved NN interpolators include: (1) NN based on deterministic confidence region (DCR), DCRNN; (2) NN based on stochastic confidence(More)
In order to reduce registration time, improve convergence ability and perform better in the presence of noise, a novel medical image registration measure is proposed, which is called generalized Jensen-Schur measure. According to Jensen-Schur measure, two kinds of special measures are constructed: Jensen-Schur- alpha and Jensen-Rényi-alpha. The(More)
A novel method for high-dimensional mutual information registration is proposed. This method first calculates high-dimensional mutual information matrix, and then calculates the entropy of that matrix. The maximal entropy corresponds to the optimal registration solution. The method was qualitatively and quantitatively evaluated on simulated and real brain(More)
As a similarity measure of medical image registration, f-information is studied. Mutual information is considered a special type of f-information. In order to reduce sensitivity to changes in overlap, two novel normalized I-alpha-information measures are proposed. The function curves, computational time and convergence are studied by applying these measures(More)
In the presence of spatially-varying illumination changes, many intensity-based similarity measures cannot capture the complex interactions among the pixel intensities and result in wrong registration. Residual complexity (RC) measure can solve this problem and provide accurate and robust registration results in the same modality images registration. In(More)
  • Shunbo Hu
  • 2010 3rd International Conference on Biomedical…
  • 2010
When using conditional multi-resolution analysis of uniform space sub sampling, the important edge information will be lost in image registration based on intensity, which will result many local maxima and wrong registration. In order to solve the above problem, the non-uniform multi-resolution analysis method is proposed, which is based on sub sampling(More)
Robust visual tracking, as a critical problem in community of computer vision, is still knotty, especially in challenging scenarios. In this paper, using the nature of low-rank matrix recovery, we propose a tracker with structured appearance model consisting of multiple representative models. By exploring the signal recovery power of Low-Rank matrix, we get(More)
PURPOSE Many brain development studies have been devoted to investigate dynamic structural and functional changes in the first year of life. To quantitatively measure brain development in such a dynamic period, accurate image registration for different infant subjects with possible large age gap is of high demand. Although many state-of-the-art image(More)
PURPOSE Accurately analyzing the rapid structural evolution of human brain in the first year of life is a key step in early brain development studies, which requires accurate deformable image registration. However, due to (a) dynamic appearance and (b) large anatomical changes, very few methods in the literature can work well for the registration of two(More)
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