Wang Tianfu

Edge Enhancement and Filtering of Medical Ultrasonic Images Using a Hybrid Method

A hybrid method based on anisotropic diffusion (AD) is proposed for ultrasound speckle suppression and edge enhancement. This method is designed to utilize the different denoising properties of three techniques: median filtering, improved AD filtering and isotropic diffusion filtering. The gradient matrix is analyzed, and thresholds are chosen by experiments. The hybrid method is made by combining the three filtering methods for three different grayscale gradient ranges respectively. The filtering program is realized by iteration, with iteration time determined by iteration stopping criterion (ISC) accurately. In the experiment hundreds of images are processed by hybrid method, in contrast with median filtering and speckle reducing anisotropic diffusion (SRAD) filtering. The experimental results shows hybrid method can greatly improve processing speed, while successfully suppress speckle and enhance edge, therefore suitable for high-speed noise elimination of 3D images with huge data.

Segmentation of Medical Ultrasound Image Based on Markov Random Field

Segmentation is a most important but difficult step in ultrasound image analysis. For the speckle noise and the tissue intensity inhomogeneities in the medical ultrasound images, the conventional segmentation approaches based on intensity or intensity-statistics do not work well. Current studies to reduce the speckle noise are failed in boundary preserving. And the researches on intensity inhomogeneites can not obtain the complete structure. In this paper, a new segmental method combined Markov random field (MRF) model with morphological image processing is proposed to cover the shortages above. MRF step is used to estimate the label image and morphological image processing makes the region-of-interest (ROI) complete to get a complete tissue. This algorithm is insensitive to speckle noise. Experimental results on synthetic images and ultrasound images show that this algorithm works successfully in MRF model and can correctly identify the tissues in the medical ultrasound images.

Quantification of Eccentric Mitral Regurgitation by Regurgitant Volume

To investigate and verify that real-time 3-dimensional (RT-3D) color Doppler is capable of quantifying the eccentric miral regurgitation (MR) by computing regurgitant volume (RV). 34 patients (mean age 37.13 plusmn 18.28 years) with confirmed eccentric MR were undergone RT-3D echocardiography. By the spatial and temporal integration of the cross-sectional velocity distribution of regurgitant valve, the systolic RV can be evaluated. Then RV were applied to assessing the severity of eccentric MR and compared with the jet volume (JV) and the vena contracta width (VCW) immediately measured. In 34 patients, 2 patients were graded as mild, 16 patients as moderate, and 16 patients as severe. Our RV measurements have good correlation with JV(r=0.9453) and VCW(r=0.8829) respectively. RT-3D color Doppler echocardiography was capable of quantifying the RV of the eccentric MR.