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Non-negative matrix factorization (NMF) is a good partsbased representation in computer vision. However, it fails to preserve or enhance the features and details of the data. To resolve this problem, we propose a novel sparse matrix factorization method for medical image registration, called Total Variation constrained Graph regularized Nonnegative Matrix Factorization (TV-GNMF). We incorporate total...
PET/CT image fusion has emerged as a new and promising research area in recent years, whereas the current standard method for PET/CT fusion, Alpha-blending, often blurs fine anatomical structure. In this paper, a new fusion method based on the Pansharp model is presented. Our proposed method consists of first up-scaling the PET image to the resolution of the CT data by bilinear interpolation and registering...
In this paper, we propose a new method for the extraction of blood vessels in retinal images. This approach starts with a Hessian-based multiscale filtering method to enhance blood vessels in gray retinal images. Subsequently, a new radial symmetry transformation, which is based on line kernels, is proposed to improve the detection of vessel structures and restrain the response of nonvessel structures...
The sustained effects of acupuncture have been widely applied to clinical treatment, thus it can be assumed that the relatively functional specificity of acupoints may evolve as the function of time. In this study, we originally combined ICA and multivariate Granger causality analysis to explore the causal interactions within and among the post-acupuncture resting-state networks (RSNs) at a hearing-related...
Acupoint specificity, lying at the core of the Traditional Chinese Medicine, still faces many controversies. As previous neuroimaging studies on acupuncture mainly adopted relatively low time-resolution functional magnetic resonance imaging (fMRI) technology and inappropriate block-designed experimental paradigm due to sustained effect, in the current study, we employed a single block-designed paradigm...
Previous neuroimaging studies on acupuncture have primarily adopted functional connectivity analysis associated with one or a few preselected brain regions. Few have investigated how these brain regions interacted at the whole brain level. In this study, we sought to investigate the acupoint specificity by exploring the whole brain functional connectivity analysis on the post-stimulus resting brain...
Bioluminescence imaging (BLI) offers an alternative opportunity for non-invasively visualizing biological processes at the physiological and molecular levels in whole animals. Tomographic bioluminescence imaging (TBI) can further translate planar imaging into three-dimensional quantitative bioluminescent source distribution. Although many reconstruction methods have been developed, efforts are still...
In this paper, a local hybrid level-set method for medical image segmentation is presented. In proposed method, a locally fitted binary energy function is introduced into the hybrid level-set framework proposed by Zhang et al.. Compared with the globally specified threshold, the use of local binary fitting energy in the hybrid level-set method allows one to extract local image information more accurately,...
Volume rendering techniques have been used widely for high quality visualization of 3D data sets, especially in the fields of biomedical image processing. However, when rendering very large (out-of-core) volume data sets, the conventional in-core volume rendering algorithms cannot run efficiently due to the impossibility of fitting the entire input data in the internal memory of a computer. In order...
The design of software platform for medical imaging application has been increasingly prioritized as the sophisticated application of medical imaging. With this demand, we have designed and implemented a novel software platform in traditional object-oriented fashion with some common design patterns. This platform integrates the mainstream algorithms for medical image processing and analyzing within...
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