Biomedical subjects

Huazhong Shu

Publications and source records attributed to Huazhong Shu.

6 recordsLinked to original sources

PubMed2007

Image description with generalized pseudo-Zernike moments.

A new set, to our knowledge, of orthogonal moment functions for describing images is proposed. It is based on the generalized pseudo-Zernike polynomials that are orthogonal on the unit circle. The generalized pseudo-Zernike polynomials are scaled to ensure numerical stability, and some properties are discussed. The performance of the proposed moments is analyzed in terms of image reconstruction capability and invariant character recognition accuracy. Experimental results demonstrate the superiority of generalized pseudo-Zernike moments compared with pseudo-Zernike and Chebyshev-Fourier moments in both noise-free and noisy conditions.

Journal Article↗

PubMed2006

Image reconstruction for positron emission tomography using fuzzy nonlinear anisotropic diffusion penalty.

Iterative algorithms such as maximum likelihood-expectation maximization (ML-EM) become the standard for the reconstruction in emission computed tomography. However, such algorithms are sensitive to noise artifacts so that the reconstruction begins to degrade when the number of iterations reaches a certain value. In this paper, we have investigated a new iterative algorithm for penalized-likelihood image reconstruction that uses the fuzzy nonlinear anisotropic diffusion (AD) as a penalty function. The proposed algorithm does not suffer from the same problem as that of ML-EM algorithm, and it converges to a low noisy solution even if the iteration number is high. The fuzzy reasoning instead of a nonnegative monotonically decreasing function was used to calculate the diffusion coefficients which control the whole diffusion. Thus, the diffusion strength is controlled by fuzzy rules expressed in a linguistic form. The proposed method makes use of the advantages of fuzzy set theory in dealing with uncertain problems and nonlinear AD techniques in removing the noise as well as preserving the edges. Quantitative analysis shows that the proposed reconstruction algorithm is suitable to produce better reconstructed images when compared with ML-EM, ordered subsets EM (OS-EM), Gaussian-MAP, MRP, TV-EM reconstructed images.

Algorithms↗

PubMed2006

Bayesian algorithms for PET image reconstruction with mean curvature and Gauss curvature diffusion regularizations.

The basic mathematical problem behind PET is an inverse problem. Due to the inherent ill-posedness of this inverse problem, the reconstructed images will have noise and edge artifacts. A roughness penalty is often imposed on the solution to control noise and stabilize the solution, but the difficulty is to avoid the smoothing of edges. In this paper, we propose two new types of Bayesian one-step-late reconstruction approaches which utilize two different prior regularizations: the mean curvature (MC) diffusion function and the Gauss curvature (GC) diffusion function. As they have been studied in image processing for removing noise, these two prior regularizations encourage preserving the edge while the reconstructed images are smoothed. Moreover, the GC constraint can preserve smaller structures which cannot be preserved by MC. The simulation results show that the proposed algorithms outperform the quadratic function and total variation approaches in terms of preserving the edges during emission reconstruction.

Algorithms↗

PubMed2006

General method to derive the relationship between two sets of Zernike coefficients corresponding to different aperture sizes.

Zernike polynomials have been widely used to describe the aberrations in wavefront sensing of the eye. The Zernike coefficients are often computed under different aperture sizes. For the sake of comparison, the same aperture diameter is required. Since no standard aperture size is available for reporting the results, it is important to develop a technique for converting the Zernike coefficients obtained from one aperture size to another size. By investigating the properties of Zernike polynomials, we propose a general method for establishing the relationship between two sets of Zernike coefficients computed with different aperture sizes.

Journal Article↗

PubMed2003

A vectorized Monte Carlo code for radiotherapy treatment planning dose calculation.

How to speed up Monte Carlo (MC) simulation in dose calculation without losing its intrinsic accuracy is one of the key issues of making a clinical MC dose engine. In this study we intensively investigated a special parallel computation technique, the vectorization technique, to boost simulation efficiency on a personal computer (PC) without extra hardware investment. A MC code, dose planning method (DPM), was extensively modified into a vectorized code, V-DPM, using the streaming single-instruction-multiple-data extension (SSE) parallel computation model. Comparative simulations were conducted for typical simulation cases in both DPM and V-DPM codes. We found that in every case the V-DPM code runs 1.5 times faster than the DPM code with variance of 0.6%.

Algorithms↗

PubMed2003

String matching techniques for high-level primitive formation in 2-D vascular imaging.

This paper deals with a so-called "intermediate" description, in other words, the formation of high-level primitives in angiographies. The method is based on an attributed string matching technique capable to capture the shape similarities between low-level primitives (i.e., vessel contours and centerlines). After designing a multiparametric cost function, we propose a multiline pairing algorithm. In order to objectively evaluate its performances, results are first provided on simulated data and then on a set of coronarographic images, where it is shown that anatomically coherent entities like vessel segments and branches can be built, "objects" that can be further individually analyzed for clinical purpose.

Algorithms↗