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Identification of cancer susceptibility genes through the study of site-specific cancer families has resulted in tremendous insight into the molecular mechanisms underlying carcinogenesis in organs such as the breast, colon, and kidney. Although progress in this area for prostate cancer has been slow, extensive evidence exists to support an important genetic component of prostate cancer susceptibility. This chapter will review the progress and difficulties presented in the search for prostate cancer susceptibility alleles in prostate cancer families. Two genes identified in family studies, RNASEL and MSR1, although showing relatively weak associations with prostate cancer overall, implicate genetic variation in the inflammatory response as a possibly critical pathway in modifying risk for this common cancer. As with many other cancers, inherited defects in DNA repair pathways seem to result in some familial clustering of prostate cancer. Studies underway and planned that emphasize potentially more homogeneous subsets of prostate cancer, and that take advantage of methodological and technological advances to detect weaker genetic influences should prove valuable in accelerating the rate of progress in this area. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel approach for real-time simulation of deformable soft-tissue. The framework includes segmentation of medical data, physical and mathematical modeling, performance optimization as well as collision detection. The physical and mathematical modeling which is the most significant phase in the approach is based on an improved elasticity theory which uses the skeleton structure of the deformable object to reflect volumetric information. We also refine the model to satisfy the real-time computation requirement and achieve a reasonable deformation effect on the global level as well as the local region by introducing the concepts of the angular spring, the return spring and the local deformation concept. A model based on real clinical data using a segmented left kidney and a collision detection demo are presented as an example in our case study. [ABSTRACT FROM AUTHOR]

Real-time simulation for global deformation of soft tissue, using Mass-Spring or traditional finite element method (FEM), is difficult because of the following reasons: (1) The linear elastic model is inappropriate for simulating large deformation for the probably unreasonable distortion; (2) The size of the 3D problem (the number of elements in the Mass-Spring or FEM mesh) is much larger than a 2D issue. In this paper, we propose a novel approach for these 2 problems: (1) deploying a deformable centerline, combined with medial representation method instead of the traditional linear elastic model, to simulate large motion and global deformation of a 3D tube like object; (2) applying a simplified algorithm which reconstructs the soft tissue surface by the medial representation method and reduces the complexity of a 3D problem. [ABSTRACT FROM AUTHOR]

3D video, which is composed of a sequence of mesh models and can provide the user with interactivity, is attracting increasing attention in many research groups. However, it is time-consuming and expensive to generate 3D video sequences. In this paper, a motion composition method is proposed to edit 3D video based on the user's requirements so that 3D video can be re-used. By analyzing the feature vectors, the hierarchical motion structure is parsed and then a motion database is set up by selecting the representative motions. A motion graph is constructed to organize the motion database by finding the possible motion transitions. Then, the best path is searched based on a proposed cost function by a modified Dijkstra algorithm after the user selects the desired motions in the motion database, which are called key motions in this paper. Our experimental results show the edited 3D video sequence looks natural and realistic. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel deformable model for soft tissue simulation in a real-time manner. The innovative model consists of two sub-models: the surface one and the internal one, which are based on Mass-Spring system and Medial Representation respectively. This proposed model is more accurate and efficient than the pure surface Mass-Spring one by taking advantages of Medial Representation to reflect inner attributes of soft tissue. We also optimize the Mass-Spring system in order to refine the appearance of soft tissue movement and reduce its complexity. A real clinical model using a segmented left-kidney is presented as an example in our case study. [ABSTRACT FROM AUTHOR]

Video captions can be used to index large video archives in digital libraries. In this paper, an algorithm for detecting captions in video frames using support vector machine (SVM) is proposed. First, the input video frame is divided into square sub-blocks and a trained SVM is used to identify whether each sub-block is a caption block or not. Second, horizontal projection and vertical projection are performed to locate the candidate caption regions. Finally, false alarms are reduced by caption region verification. Experimental results show that the algorithm has a low missed rate and false alarm rate. [ABSTRACT FROM AUTHOR]

An evaluation of two traditional segmentation algorithms of Morphological Reconstruction and the Fast Marching method along with a novel hybrid segmentation approach is presented. After introducing the Fast Marching and the Morphological Reconstruction segmentation, we propose a novel hybrid segmentation approach in multi-stage, which is derived from both an improved Fast Marching method and the Morphological Reconstruction. To demonstrate the effectiveness and accuracy of the three methods, we employ an MRI brain image in our experiments, in which "gold standard" is known. The evaluation is measured accordingly in accuracy and speed when running a 2.0 GHz based windows XP PC. The accuracy results of average 0.9738, 0.6302 and 0.9734 measured in similarity indexes of the Morphological Reconstruction, the Fast Marching and the hybrid approach are achieved, respectively. The computing performance required 188.6, 22.3 and 43.4 in seconds accordingly. [ABSTRACT FROM AUTHOR]