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A new reversible 3D mesh watermarking scheme is proposed in conjunction with progressive compression. Progressive 3D mesh compression permits a progressive refinement of the model from a coarse to a fine representation by using different levels of detail (LoDs). A reversible watermark is embedded into all refinement levels such that (1) the refinement(More)
In this paper, we present two methods to compress colored 3D triangular meshes in a progressive way. Although many progressive algorithms exist for efficient encoding of connectivity and geometry, none of these techniques consider the color data in spite of its considerable size. Based on the powerful progressive algorithm from Alliez and Desbrun [All01a],(More)
The classification information model or CIM classifies instances by considering the discrimination ability of their features, which was proven to be useful for word sense disambiguation at SENSEVAL-1. But the CIM has a problem of information loss. KUNLP system at SENSEVAL-2 uses a modified version of the CIM for word sense disambiguation. We used three(More)
Présentée en vue d'obtenir le grade de Docteur, spécialité Informatique par Ho LEE Compression progressive et tatouage conjoint de maillages surfaciques avec attributs de couleur Abstract The use of 3D models, represented as a mesh, is growing in many applications. For efficient transmission and adaptation of these models to the heterogeneity of client(More)
PURPOSE SIRT1 (silent mating-type information regulation 2 homologue 1) expression has been reported to predict poor survival in some cancers. We therefore investigated the expression levels of SIRT1 and its negative regulator, DBC1 (deleted in breast cancer 1), in gastric cancer patients. EXPERIMENTAL DESIGN We evaluated immunohistochemical expression of(More)
We propose a new lossless progressive compression algorithm based on rate-distortion optimization for meshes with color attributes; the quantization precision of both the geometry and the color information is adapted to each intermediate mesh during the encoding/decoding process. This quantization precision can either be optimally determined with the use of(More)
In this paper, we propose an efficient semi-automatic liver segmentation method from contrast-enhanced computed tomography (CT) images. We exploit level-set speed images to define an approximate initial liver shape. The first step divides a CT image into a set of discrete objects based on the gradient information, which is normalized on the speed image. The(More)
Automatic liver segmentation is difficult because of the wide range of human variations in the shapes of the liver. In addition, nearby organs and tissues have similar intensity distributions to the liver, making the liver's boundaries ambiguous. In this study, we propose a fast and accurate liver segmentation method from contrast-enhanced computed(More)
Recently, the possibility of PD1 pathway-targeted therapy has been extensively studied in various human malignant tumors. However, no previous study has investigated their potential application for soft-tissue sarcomas (STS). In this study, we evaluated the clinical impact of intra-tumoral infiltration of PD1-positive lymphocytes and PD-L1 expression in(More)
We propose a new connectivity-based progressive compression approach for triangle meshes. The key idea is to adapt the quantization precision to the resolution of each intermediate mesh so as to optimize the rate-distortion trade-off. This adaptation is automatically determined during the encoding process and the overhead is efficiently encoded using(More)