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Wu-fan Chen

Publications and source records attributed to Wu-fan Chen.

12 recordsLinked to original sources
PubMed2006

[A level set method based on Hermite derivative filter for segmentation of magnetic resonance images].

A level set segmentation algorithm based on Hermite derivative filter is proposed for segmentation of human magnetic resonance images (MRI). Instead of utilizing the traditional first difference, Hermite derivative filter was used to calculate the differential coefficients in the course of level set interface evolution, so that the differential coefficients were no longer decided by the first neighbor, but by the second neighbor of the examined pixel. Results of the segmentation tests proved that to the same segmentation process, the level set method utilizing Hermite derivative filter produced a more accurate result. The proposed method showed special superiority over the conventional method for images with interferences by noise. At the same time, the new algorithm did not increase the time for the segmentation.

Algorithms↗
PubMed2006

[Real-time volume rendering of medical 3D dynamic ultrasound].

Dynamic 3D ultrasound is a very promising technology for clinical use, but not being a Cartesian 3D dataset, 3D ultrasound data can not be visualized directly with real-time volume rendering accelerated by 3D texture hardware. In this paper, fast volume rendering using 3D texture hardware acceleration is introduced and modern PC graphics card architecture analyzed. A modified method is proposed to obtain real-time volume rendering of dynamic 3D ultrasound data by programming vertex shader in GPU. Experimental results show that 3D ultrasound data can be rendered with real-time speed in normal PC platform. The method can be widely applied in future 3D dynamic ultrasound clinical research.

Algorithms↗
PubMed2006

[Noise image segmentation based on generalized fuzzy Gibbs random field].

In order to segment the blurred image with large noise, the authors propose a new Bayesian image segmentation method based on generalized fuzzy Gibbs random field. Based on the generalized fuzzy set, the new method introduces generalized fuzzy membership into Gibbs potential function and the potential function is redefined to obtain the new segmentation model. The optimal processing is executed through iterative conditional modes (ICM). The experiment results showed that the new approach could effectively segment the degenerated images.

Algorithms↗
PubMed2006

[Fuzzy Markov random filed model and a new algorithm for image segmentation].

A fuzzy Markov random field (FMRF) model is established and a new algorithm based on FMRF for image segmentation proposed in this paper. This algorithm simultaneously deals with the fuzziness and randomness for effective acquisition of the prior knowledge of the images. A conventional Markov random field (CMRF) serves as a bridge between the FMRF, obviously a generalization of the CMRF, and the original images. The FMRF degenerates into the CMRF when no fuzziness is considered. The segmentation results are obtained by fuzzifying the image, updating the membership of prior FMRF based on the maximum posteriori criteria, and defuzzifying the image according to the maximum membership principle. The proposed algorithm can effectively filter the noise and eliminate partial volume effect when processing the degraded image to ensure more accurate image segmentation.

Algorithms↗
PubMed2006

[A new mixing rigid-elastic multiresolution algorithm for medical image registration].

We present a new mixing rigid-elastic multiresolution algorithm for medical image registration from global registration to local registration in sequence. The global registration is achieved by the method of affine transformation composed of B spline, which knots are the four vertexes of the medical image. When increasing the number of the knots of the B spline along the X and Y axis, the transformation function will be more complex and "elastic", which can complete the elastic aligning for the detail of the medical image. The results of experiment demonstrated that the presented algorithm was more robust than the previous elastic algorithm of registration.

Algorithms↗
PubMed2006

[An adaptive criterion for cluster number estimation and the optimal algorithm for image segmentation].

In the algorithms for image segmentation, the number of clusters (NOC), which impacts on the segmentation results, should be first solved, and its correct estimation both theoretically and in application is of much importance. The authors propose an adaptive total energy criterion (ATEC) based on Markov random fields (MRF). The correct NOC of different images can be obtained by minimizing the ATEC and the parameters in the criterion are estimated by expectation maximization algorithm and maximum pseudo-likelihood method. The experiments show that the NOC can be automatically detected by adjusting the parameters, and the segmentation with the estimated NOC can be obtained by the maximum a posteriori at the same time.

Algorithms↗
PubMed2005

[Three-dimensional reconstruction of human organs based on magnetic resonance imaging data].

OBJECTIVE: To build proper three-dimensional models of human organs for radiation dose calculation. METHOD: Human organ models were built by contour reconstruction algorithm conforming to 4 criteria. The contours of the organs were extracted based on the contours of the reconstructed organ surfaces, and the three-dimensional models with smooth surface, exact structure and good visibility were completed by computer graphic techniques such as lighting, smoothing, and normal average. RESULT AND CONCLUSION: Several organ models were successfully reconstructed, suggesting that this method is suitable for building three-dimensional digital human organ models which can meet the need for dose calculation.

Humans↗
PubMed2005

[Inverse iterative correction for translational motion artifact of magnetic resonance imaging based on histogram entropy minimization].

During the acquisition of a magnetic resonance images (MRI), blurring and ghosting artifacts caused by the patient's motion can seriously affect the result of diagnosis. A novel automatic post-processing strategy, inverse iterative correction (IIC), has been developed to suppress MRI artifacts due to the object's in-plane rigid-body motion. By means of the proposed histogram-based entropy function, IIC method uses two successive steps to reduce the simulated motion artifacts: first, the inverse phase errors are added to all possible simulated patient's motion directions, and in the second step, the actual directions and displacement from the patient's motion are estimated to properly correct the phase, hence remove the artifacts after searching all the trial directions. To verify its feasibility, the proposed method was used to reduce rigid-motion artifacts due to simulated motion in MRI images. The experimental results showed that the new algorithm significantly outperforms over the entropy auto-focus compensation algorithm on the quality of corrections for the motion artifacts and computational cost.

Algorithms↗
PubMed2004

A fast sequential image fractal coding approach based on optimal fuzzy clustering.

To reduce the coding time of the conventional method, a fast sequential image fractal compression algorithm was proposed on the basis of the principle of optimal fuzzy clustering (OFC) for an unsupervised sample set with the category number settled by the algorithm itself. We utilized the cost function defined by the OFC algorithm to obtain the best category number corresponding to the minimum value of the function. Firstly the Linde-Buzo-Gray (LBG) algorithm was realized to acquire a rough cluster of the domain pool. Then the optimal category number was obtained by implementing our algorithm with small computational cost. Finally the more precise category was gained and the detail of the reconstructed image efficiently preserved. As a global optimal algorithm, OFC not only helps LBG eliminate the local minima, but also effectively compensates for the arbitrary interference in hard clustering problem. Soft clustering of the domain blocks allows classified searches instead of global ones and takes less coding time, and therefore clearly outperforms to the classic method relying on reduction of the size of the domain pool by classification. In computer simulation, OFC-based algorithm for the fractal coding scheme achieved excellent performance. For some standard and sequential medical images, the results denoted that the encoding speed was improved by about 5 folds without affecting the signal-to-noise ratio and compression ratio, and the quality of the reconstructed image could be better retained.

Algorithms↗
PubMed2004

[Automatic feature extraction and new method for retrieval from CT image database].

OBJECTIVE: To propose a new method for content-based retrieval from medical CT image database on the basis of automatically extracted features of the images. METHODS: An automatic feature extraction method is proposed based on expectation-maximization algorithm. A CT image is represented by a set of regions, each of which is characterized by a fuzzy regional feature vector reflecting the grey level, texture, shape, and the cumulative distribution histogram feature of the region of interest (ROI) to efficiently describe the difference between the ROIs. RESULTS: Compared with the submitted query image, the target images were retrieved in the order of similarity calculated by the proposed similarity measures. CONCLUSION: The proposed technique for CT image retrieval is suitable for clinical application, with greater precision and efficiency for retrieval than the conventional methods.

Algorithms↗
PubMed2004

[Dynamic contour tracking of medical images based on improved particle filter].

In the research of medical image processing, motion estimation and tracking relating to the region of interest has been given considerable attention. For improving the quality of the noisy or cluttered medical images, the particle filter (PF) based on the non-linear and non-Gaussian Bayesian State Estimation is a better as well as a technically challenging solution. As the algorithm of particle weights, especially the importance density function, often severely affects the performance of the PF, we propose in this paper a better algorithm for its improvement; in addition, to ensure better tracking of the dynamic contour with the PF, we proposed a new algorithm for the likelihood and prior probability density. Objective theoretical evaluation and substantial comparative experiments suggest that this method can be a good solution for accurate dynamic contour tracking.

Algorithms↗