Lishui Cheng

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Image segmentation is an important research topic in image processing and computer vision community. In this paper, we present a novel segmen-tation method based on the combination of fuzzy connectedness and adaptive fuzzy C means (AFCM). AFCM handles intensity inhomogeneities problem in magnetic resonance images (MRI) and provides effective seeds for fuzzy(More)
In simultaneous dual-isotope myocardial perfusion SPECT (MPS) imaging, data are simultaneously acquired to determine the distributions of two radioactive isotopes. The goal of this work was to develop penalized maximum likelihood (PML) algorithms for a novel cross-tracer prior that exploits the fact that the two images reconstructed from simultaneous(More)
Brain MR image segmentation is an important research topic in medical image analysis area. In this paper, we propose an active contour model for brain MR image segmentation, based on a generalized level set formulation of the Mumford-Shah functional. The model embeds explicitly gradient information into the Mumford-Shah functional, and incorporates in a(More)
Object extraction or image segmentation is a basic problem in image analysis and computer vision. It has been dealt with in various forms. Varia-tional method is an emerging framework to tackle such problems where the aim is to create an image partition that follows the data while at the same time preserving certain regularity. In this paper, we propose a(More)
In radiopharmaceutical therapy, an understanding of the dose distribution in normal and target tissues is important for optimizing treatment. Three-dimensional (3D) dosimetry takes into account patient anatomy and the nonuniform uptake of radiopharmaceuticals in tissues. Dose-volume histograms (DVHs) provide a useful summary representation of the 3D dose(More)
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