In order to perform a high-quality interactive rendering of large medical data sets on a single off-the-shelf PC, a LOD selection algorithm for multi-resolution volume rendering using 3D texture mapping is presented, ...
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In order to perform a high-quality interactive rendering of large medical data sets on a single off-the-shelf PC, a LOD selection algorithm for multi-resolution volume rendering using 3D texture mapping is presented, which uses an adaptive scheme that renders the volume in a region-of-interest at a high resolution and the volume away from this region at lower resolutions. The algorithm is based on several important criteria, and rendering is done adaptively by selecting high-resolution cells close to a center of attention and low-resolution cells away from this area. In addition, our hierarchical level-of-detail representation guarantees consistent interpolation between different resolution levels. Experiments have been applied to a number of large medical data and have produced high quality images at interactive frame rates using standard PC hardware.
Orientation field is one of the intrinsic charac-teristics of fingerprints, and it plays very important role in many processing phases of fingerprint recognition such as enhancement, minutiae extraction and matching. ...
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ISBN:
(纸本)9781467321969
Orientation field is one of the intrinsic charac-teristics of fingerprints, and it plays very important role in many processing phases of fingerprint recognition such as enhancement, minutiae extraction and matching. Therefore, accurate estimation of orientation filed is much necessary. In this paper, a novel PDE-based method is proposed for regularization of orientation field for low-quality fingerprint images. The method consists of four steps. Firstly, the coarse orientation field is computed using traditional gradient-based approach. Secondly, the reliability map of the orientation field is computed based on a procedure of multiscale coherence analysis. Then the orientation in the low-reliable region is reconstructed with the surrounding data by means of image inpainting technique. Finally, nonlinear diffusion filtering with adaptive diffusivity is performed on the whole orientation field. Experiments on the NIST SD4 fingerprint database indicated that the proposed algorithm is capable to estimate the orien-tation field accurately, especially for poor-quality fingerprints, and it can be integrated into fingerprint recognition systems to improve the performance.
A neural network appraoch for classification using features extracted by a mapping is presented. When the number of sample dimensions is much larger than the number of classes and no deviations are given but the means...
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A neural network appraoch for classification using features extracted by a mapping is presented. When the number of sample dimensions is much larger than the number of classes and no deviations are given but the means of classes, a mapping from class space to a new one whose dimensions is exactly equal to the number of classes is proposed. The vectors in the new space are considered as the feature vectors to be inputted to a neural network for classification. The property that the mapping does not change the separability of the original classification problem is given. Simulation results for object recognition are presented.
In this paper, we introduce a novel class of coplanar conics, the pencil of which can doubly contact to calibrate camera and estimate pose. We first analyze the properties of con-axes and con-eccentricity ellipses, wh...
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In this paper, we introduce a novel class of coplanar conics, the pencil of which can doubly contact to calibrate camera and estimate pose. We first analyze the properties of con-axes and con-eccentricity ellipses, which consist of a naturM extending pattern of concentric circles. Then the general case that two ellipses have two repeated complex intersection points is presented. This degenerate configuration results in a one-parameter family of homographies which map the planar pattern to its image. Although it is unable to compute the complete homography, an indirect 3-degree polynomial or 5-degree polynomial constraint on intrinsic parameters from one image can also be used for camera calibration and pose estimation under the minimal conditions. Furthermore, this nonlinear problem can be treated as a polynomial optimization problem （POP） and the global optimization solution can be also obtained by using SparsePOP （a sparse semidefinite programming relaxation of POPs）, Finally, the experiments with simulated data and real images are shown to verify the correctness and robustness of the proposed technique.
In this paper we discuss using the stratified ATMS to realize explanation-based learning. As the stratified ATMS can record and maintain the reasonings for beliefs efficiently and can deal with nonmonotonic reasoning,...
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In this paper we discuss using the stratified ATMS to realize explanation-based learning. As the stratified ATMS can record and maintain the reasonings for beliefs efficiently and can deal with nonmonotonic reasoning, so the ATMS-based EBL system can improve the efficiency of explanation-based learning, deal with multiple explanation problems in learning from imperfect theories by prioritized reasoning and multiple example verification and can give biases for induction in integrated learning. Copyright (C) 1996 Elsevier Science Ltd
A new trend in the development of medical imageprocessing systems is to enhance the shar-ing of medical resources and the collaborative processing of medical specialists. This paper presents an architecture of medica...
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A new trend in the development of medical imageprocessing systems is to enhance the shar-ing of medical resources and the collaborative processing of medical specialists. This paper presents an architecture of medical image dynamic collaborative processing on the distributed environment by combining the JAVA, CORBA (Common Object Request and Broker Architecture) and the MAS (Multi-Agents System) collaborative mechanism. The architecture allows medical specialists or applications to share records and cornmunicate with each other on the web by overcoming the shortcut of traditional approach using Common Gateway Interface (CGI) and client/server architecture, and can support the remote heterogeneous systems collaboration. The new approach im-proves the collaborative processing of medical data and applications and is able to enhance the in-teroperation among heterogeneous system. Research on the system will help the collaboration and cooperation among medical application systems distributed on the web, thus supply high quality medical service such as diagnosis and therapy to practicing specialists regardless of their actual geo-graphic location.
Since in most blind source separation(BSS)algorithms the estimations of probability density function(pdf)of sources are fixed or can only switch between one sup-Gaussian and other sub-Gaussian model,they may not be ef...
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Since in most blind source separation(BSS)algorithms the estimations of probability density function(pdf)of sources are fixed or can only switch between one sup-Gaussian and other sub-Gaussian model,they may not be efficient to separate sources with different *** to solve the problem of pdf mismatch and the separation of hybrid mixture in BSS,the generalized Gaussian model(GGM)is introduced to model the pdf of the sources since it can provide a general structure of univariate *** great advantage is that only one parameter needs to be determined in modeling the pdf of different sources,so it is less complex than Gaussian mixture *** using maximum likelihood(ML)approach,the convergence of the proposed algorithm is *** computer simulations show that it is more efficient and valid than conventional methods with fixed pdf estimation.
The sensitivity of diffuse optical tomography （DOT） imaging exponentially decreases with the increase of photon penetration depth, which leads to a poor depth resolution for DOT. In this letter, an exponential adjus...
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The sensitivity of diffuse optical tomography （DOT） imaging exponentially decreases with the increase of photon penetration depth, which leads to a poor depth resolution for DOT. In this letter, an exponential adjustment method （EAM） based on maximum singular value of layered sensitivity is proposed. Optimal depth resolution can be achieved by compensating the reduced sensitivity in the deep medium. Simulations are performed using a semi-infinite model and the simulation results show that the EAM method can substantially improve the depth resolution of deeply embedded objects in the medium. Consequently, the image quality and the reconstruction accuracy for these objects have been largely improved.
Support vector machine (SVM), as a novel approach in patternrecognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with ...
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Support vector machine (SVM), as a novel approach in patternrecognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with the nearest neighbor classifier (NNC) is proposed. The principal component analysis (PCA) is used to reduce the dimension and extract features. Then one-against-all stratedy is used to train the SVM classifiers. At the testing stage, we propose an al-
To modeling and classify underwater sound, hidden Markov tree (HMT) model in wavelet domain is adopted. Taking advantage of the models, the simulation time sequence of ocean noise can be produced. An improved classifi...
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