Problems common to the visualization in multimodal clinical environments are presented. Three different solutions for the visualization of 3D multimodal clinical data are proposed, having in mind the constrains relate...
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Problems common to the visualization in multimodal clinical environments are presented. Three different solutions for the visualization of 3D multimodal clinical data are proposed, having in mind the constrains related to the interactivity goal. Some resulting images containing this type of data in an integrated form are presented.
This paper describes the design, implementation and preliminary results of a technique for creating a comprehensive probabilistic atlas of the human brain based on high-dimensional fluid transformations. The goal of t...
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ISBN:
(纸本)3540616497
This paper describes the design, implementation and preliminary results of a technique for creating a comprehensive probabilistic atlas of the human brain based on high-dimensional fluid transformations. The goal of the atlas is to detect and quantify subtle and distributed patterns of deviation from normal anatomy, in a 3D brain image from any given subject. The algorithm analyzes a reference population of normal scans, and automatically generates color-coded probability maps of the anatomy of new subjects. Given a 3D brain image of a new subject, the algorithm calculates a set of high-dimensional volumetric maps (typically with 3842×256×3=0.1 billion degrees of freedom) fluidly deforming this scan into structural correspondence with other scans, selected one by one from an anatomic image database. The family of volumetric warps so constructed encodes statistical properties and directional biases of local anatomical variation throughout the architecture of the brain. A probability space of random transformations, based on the theory of anisotropic Gaussian random fields, is then developed to reflect the observed variability in stereotaxic space of the points whose correspondences are found by the warping algorithm. A complete system of 3842×256 probability density functions is computed, yielding confidence limits in stereotaxic space for the location of every point represented in the 3D image lattice of the new subject's brain. Color-coded probability maps are generated, densely-defined throughout the anatomy of the new subject These indicate locally the probability of each anatomic point being as unusually situated, given the distributions of corresponding points in the scans of normal subjects. 3D MRI and high-resolution cryosection volumes are analyzed, from subjects with metastatic tumors and Alzheimer's disease. Applications of the random fluid-based probabilistic atlas include the transfer of multi-subject 3D functional, vascular and histologic maps onto a si
Our goal at the University of California, San Diego, is to emphasize the increased importance of visual computing and image engineering by expanding and redesigning our curriculum. The planned curriculum development i...
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Our goal at the University of California, San Diego, is to emphasize the increased importance of visual computing and image engineering by expanding and redesigning our curriculum. The planned curriculum development includes a 1-year undergraduate sequence in image processing and machine perception, and a redesign of the current core graduate sequence to put increased emphasis on synthesis of ideas from separate areas into a core sequence of visual computing. We are also introducing many advanced courses at both the undergraduate and graduate levels.
A method to assess the error introduced in data visualization by Direct Volume Rendering (DVR) methods is proposed. Results obtained using synthetic data and two DVR methods are presented. The final goal will be compu...
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A method to assess the error introduced in data visualization by Direct Volume Rendering (DVR) methods is proposed. Results obtained using synthetic data and two DVR methods are presented. The final goal will be computing "confidence indices" that help the user to decide which visualizations of a data set to use.
The marching cubes (MC) algorithm is a method for generating isosurfaces. It also generates an excessively large number of triangles to represent an isosurface; this increases the rendering time. This paper presents a...
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ISBN:
(纸本)9780897918640
The marching cubes (MC) algorithm is a method for generating isosurfaces. It also generates an excessively large number of triangles to represent an isosurface; this increases the rendering time. This paper presents a decimation method to reduce the number of triangles generated. Decimation is carried out before creating a large number of triangles. Four major steps comprise the algorithm: surface tracking, merging, crack patching and triangulation. Surface tracking is an enhanced implementation of the MC algorithm. Starting from a seed point, the surface tracker visits only those cells likely to compose part of the desired isosurface. The cells making up the extracted surface are stored in an octree that is further processed. A bottom-up approach is taken in merging the cells containing a relatively flat approximating surface. The finer surface details are maintained. Cells are merged as long as the error due to such an operation is within a user-specified error parameter, or a cell acquires more than one connected surface component in it. A crack patching method is described that forces edges of smaller cells to lie along those of the larger neighboring cells. The overall saving in the number of triangles depends both on the specified error value and the nature of the data. Use of the hierarchical octree data structure also presents the potential of incremental representation of surfaces. We can generate a highly smoothed surface representation which can be progressively refined as the user-specified error value is decreased.
The EM algorithm promises an estimated image with the maximal likelihood for 3D PET image reconstruction. However, due to its long computation time, the EM algorithm has not been widely used in practice. While several...
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The EM algorithm promises an estimated image with the maximal likelihood for 3D PET image reconstruction. However, due to its long computation time, the EM algorithm has not been widely used in practice. While several parallel implementations of the EM algorithm have been developed to make the EM algorithm feasible, they do not guarantee an optimal parallelization efficiency. In this paper, we propose a new parallel EM algorithm which maximizes the performance by optimizing data replication on a mesh-connected message-passing multiprocessor. To optimize data replication, we have formally derived the optimal allocation of shared data, group sizes, integration and broadcasting of replicated data as well as the scheduling of shared data accesses. The proposed parallel EM algorithm has been implemented on an iPSC/860 with 16 PEs. The experimental and theoretical results, which are consistent with each other, have shown that the proposed parallel EM algorithm could improve performance substantially over those using unoptimized data replication.
A systematic conformational search was performed on a set of H/sub 1/ histamine receptor antagonists in an effort to define a pharmacophore. This study suggests that the H/sub 1/ receptor may bind antihistamines with ...
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A systematic conformational search was performed on a set of H/sub 1/ histamine receptor antagonists in an effort to define a pharmacophore. This study suggests that the H/sub 1/ receptor may bind antihistamines with two acidic moieties located between 4.97A and 6.15A from one another. Disulfide bond formation is also possible for this class of antihistamines. This, however, would not explain reversible binding unless a thioesterase is involved.
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