A framework with modified fast FCM for brain MR images segmentation

Intensity inhomogeneity, noise and partial volume (PV) effect render a challenging task for segmentation of brain magnetic resonance (MR) images. Most of the current MR image segmentation methods focus on only one or two of the effects listed above. In this paper, a framework with modified fast fuzzy c-means for brain MR images segmentation is proposed to take all these effects into account simultaneously and improve the accuracy of image segmentations. Firstly, we propose a new automated method to determine the initial values of the centroids. Secondly, an adaptive method to incorporate the local spatial continuity is proposed to overcome the noise effectively and prevent the edge from blurring. The intensity inhomogeneity is estimated by a linear combination of a set of basis functions. Meanwhile, a regularization term is added to reduce the iteration steps and accelerate the algorithm. The weights of the regularization terms are all automatically computed to avoid the manually tuned parameter. Synthetic and real MR images are used to test the proposed framework. Improved performance of the proposed algorithm is observed where the intensity inhomogeneity, noise and PV effect are commonly encountered. The experimental results show that the proposed method has stronger anti-noise property and higher segmentation precision than other reported FCM-based techniques.     

Curvature and entropy based wall boundary condition for the high order spectral volume Euler solver

A curvature and entropy based wall boundary condition is implemented in the high order spectral volume (SV) context. This method borrows ideas from the “curvature-corrected symmetry technique” developed by (Dadone A, Grossman B. Surface Boundary Conditions for Compressible Flows. AIAA J 1994; 32(2): 285–93), for a low order structured grid Euler solver. After numerically obtaining the curvature, the right state (by convention, the left state is inside the computational domain and the right state lies outside of the computational domain) face pressure values are obtained by solving a linearised system of equations. This is unlike that of the lower order finite volume and difference simulations, wherein the right state face values are trivial to obtain. The right state face density values are then obtained by enforcing entropy conservation. Accuracy studies show that simulations performed by employing the new boundary conditions deliver much more accurate results than the ones which employ traditional boundary conditions, while at the same time asymptotically reaching the desired order of accuracy. Numerical results for two-dimensional inviscid flows around the NACA0012 airfoil and over a bump with the new boundary condition showed dramatic improvements over those with the conventional approach. In all cases and orders, spurious entropy productions with the new boundary treatment are significantly reduced. In general, the numerical results are very promising and indicate that the approach has a great potential for 3D high order simulations.     

Large area forest stem volume mapping in the boreal zone using synergy of ERS-1/2 tandem coherence and MODIS vegetation continuous fields

ERS-1/2 tandem coherence was reported to have high potential for the mapping of boreal forest stem volume (e.g. Santoro et al., 2002, 2007a; Wagner et al., 2003; Askne & Santoro, 2005). Large-scale application of the data for forest stem volume mapping, however, is hindered by the variability of coherence with meteorological and environmental acquisition conditions. The traditional way of stem volume retrieval is based on the training of models, relating coherence to stem volume, with the aid of forest inventory data which is generally available for a few small test sites but not for large areas. In this paper a new approach is presented that allows model training using the MODIS Vegetation Continuous Fields canopy cover product (Hansen et al., 2003) without further need for ground data. A comparison of the new approach with the traditional regression-based and ground-data dependent model training is presented in this paper for a multi-seasonal ERS-1/2 tandem dataset covering several well known Central Siberian forest sites. As a test scenario for large-area application, the approach was applied to a multi-seasonal ERS-1/2 tandem dataset of 223 ERS-1 and ERS-2 image pairs covering Northeast China (~ 1.5 million km²) to map four stem volume classes (0-20, 20-50, 50-80, and > 80 m³/ha).     

Extracting 3D information on bone remodeling in the proximity of titanium implants in SRμCT image volumes

Bone-implant integration is measured in several ways. Traditionally and routinely, 2D histological sections of samples, containing bone and the biomaterial, are stained and analyzed using a light microscope. Such histological section provides detailed cellular information about the bone regeneration in the proximity of the implant. However, this information reflects the integration in only a very small fraction, a 10 μm thick slice, of the sample. In this study, we show that feature values quantified on 2D sections are highly dependent on the orientation and the placement of the section, suggesting that a 3D analysis of the whole sample is of importance for a more complete judgment of the bone structure in the proximity of the implant. We propose features describing the 3D data by extending the features traditionally used for 2D-analysis. We present a method for extracting these features from 3D image data and we measure them on five 3D SRμCT image volumes.We also simulate cuts through the image volume positioned at all possible section positions. These simulations show that the measurement variations due to the orientation of the section around the center line of the implant are about 30%.     

三维超音进气道系统流场计算的区域分裂算法

51．引言对于现代战斗机和飞航导弹来说,进气道的气流品质对推进系统的性能有很大的影响．进气道的气流品质不仅依赖于进气道的形状,也依赖于飞行器的前部外型和进气道的安装位置．因此,必须对前机（弹）身外流场和进气道内流场统一求解,以适应一体化设计之要求．然而统一求解三推进气道内外流场组合系统有许多困难．首先是难以生成单一的计算网格系统,其次是在很大程度上受计算机内存和运算速度的限制．统一的网格系统必然需要很大的内存．另外,由于进气道内外流场相互干扰十分强烈,在某些来流条件下,一般的统一网格极难得到收敛解…     

Interactive classification for pre-integrated volume rendering of high-precision volume data

The pre-integrated volume rendering technique is widely used for creating high quality images. It produces good images even though the transfer function is nonlinear. Because the size of the pre-integration lookup table is proportional to the square of data precision, the required storage and computation load steeply increase for rendering of high-precision volume data. In this paper, we propose a method that approximates the pre-integration function proportional to the data precision. Using the arithmetic mean instead of the geometric mean and storing opacity instead of extinction density, this technique reduces the size and the update time of the pre-integration lookup table so that it classifies high-precision volume data interactively. We demonstrate performance gains for typical renderings of volume datasets.     

Dimensional reduction of 3D building models using graph theory and its application in building energy simulation

Since the various people involved in the design process for a building project tend to hold conflicting views, this inevitably leads to a range of disparate models for planning and calculation purposes. In order to interpret the relevant geometrical, topological and semantical data for any given building model, we identify a structural component graph, a graph of room faces, a room graph and a relational object graph as aids and explain algorithms to derive these relations. We start with a building model by transferring its geometrical, topological and semantical data into a volume model, decomposing the latter into a so-called connection model and then extracting all air volume bodies and hulls of the model by means of further decomposition into elementary cyclic connection components. The technique is demonstrated within the scope of building energy simulation by deriving both a dimensionally reduced object model required for setting up a thermal multizone model and a geometrical model for defining single or multiple computational fluid dynamic domains in a building together with incidence matrices correlating these models. The algorithm is basically applicable to any building energy simulation tool.

Numerical Comparison of WENO Finite Volume and Runge–Kutta Discontinuous Galerkin Methods

High order WENO (weighted essentially non-oscillatory) schemes and discontinuous Galerkin methods are two classes of high order, high resolution methods suitable for convection dominated simulations with possible discontinuous or sharp gradient solutions. In this paper we first review these two classes of methods, pointing out their similarities and differences in algorithm formulation, theoretical properties, implementation issues, applicability, and relative advantages. We then present some quantitative comparisons of the third order finite volume WENO methods and discontinuous Galerkin methods for a series of test problems to assess their relative merits in accuracy and CPU timing.     

Efficient Compositing Methods for the Sort-Last-Sparse Parallel Volume Rendering System on Distributed Memory Multicomputers

In the sort-last-sparse parallel volume rendering system on distributed memory multicomputers, one can achieve a very good performance improvement in the rendering phase by increasing the number of processors. This is because each processor can render images locally without communicating with other processors. However, in the compositing phase, a processor has to exchange local images with other processors. When the number of processors exceeds a threshold, the image compositing time becomes a bottleneck. In this paper, we propose three compositing methods to efficiently reduce the compositing time in parallel volume rendering. They are the binary-swap with bounding rectangle (BSBR) method, the binary-swap with run-length encoding and static load-balancing (BSLC) method, and the binary-swap with bounding rectangle and run-length encoding (BSBRC) method. The proposed methods were implemented on an SP2 parallel machine along with the binary-swap compositing method. The experimental results show that the BSBRC method has the best performance among these four methods.     

A Unified Subdivision Scheme for Polygonal Modeling

Subdivision rules have traditionally been designed to generate smooth surfaces from polygonal meshes. In this paper we propose to employ subdivision rules as a polygonal modeling tool, specifically to add additional level of detail to meshes. However, existing subdivision schemes have several undesirable properties making them ill suited for polygonal modeling. In this paper we propose a general set of subdivision rules which provides users with more control over the subdivision process. Most existing subdivision schemes are special cases. In particular, we provide subdivision rules which blend approximating spline based schemes with interpolatory ones. Also, we generalize subdivision to allow any number of refinements to be performed in a single step.