A new algorithm for ultrasound image speckle suppression / 中国医疗器械杂志

Ultrasound image has a lot of speckle noise, which brings great difficulties to the feature extraction, recognition and analysis. Especially in the edge extraction, the conventional extraction algorithms are difficult to achieve the desired results because of the speckle noise. To solve this problem, an algorithm based on the anisotropic diffusion equation is presented. The new algorithm combines the robust estimation and considers the characteristic of the speckle noise, so it can suppress the speckle noise effectively and be more robust, thus the edge details of the ultrasound image can be preserved even enhanced, which can provide effective safeguard for the following edge extraction. Furthermore, the paper proposes a new method to compute speckle scale coefficients automatically, which reduces the influence of the human beings, and enhances the stability of the algorithm.

Breast tumor classification based on serial grayscale ultrasound images / 中国医疗器械杂志

This paper proposes an algorithm of evaluating the compression depth, and then to extract four normalized mammary elasticity characteristic parameters with respect to the compression depth. The classification experiments show that these elasticity parameters have a good capability in determining whether the tumor is benign or malignant, and if combined with morphological parameters, the accuracy, sensitivity and specificity can be improved and increased to 95.19%, 98.82% and 92.16%, respectively.

Three domains filtering for medical ultrasound images denoising / 中国医疗器械杂志

A filtering algorithm is proposed to deal with the medical ultrasonic image series in video format, which uses the relativity in spatial domain, gray value domain and temporal domain simultaneously. For each frame image, the relativity in spatial domain and gray value domain is utilized to construct the adaptive neighborhood first. Then the spatial weighted and gray value weighted filtering is performed in this neighborhood. Finally, the temporal relativity between the adjacent frames is used to perform the temporal weighted filtering. All the weighted filtering in the three domains uses Gaussian kernel, thus the filtering sensitivity resulting from the threshold selection is reduced, and the stability of the algorithm is enhanced. As it can be seen from the experimental results, the three-domains filtering algorithm can suppress the noise effectively, and the edge details can be reserved well. So it is useful for the feature extraction, recognition and analysis.

Segmentation of breast tumor ultrasound images based on an improved C-V model / 中国医疗器械杂志

This paper proposes an improved C-V model, which can avoid the step of re-initialization and simplify the formation of the initial level set function, thus the speed of segmentation can be accelerated greatly. Furthermore, based on the grayscale distribution characteristics of the breast tumor ultrasound images and on the hypothesis of piecewise constant in the C-V model, a semiautomatic segmentation flow has been presented, in which the rough contour is sketched first, and then a subimage would be obtained for the refined segmentation algorithm. This flow has improved not only the accuracy, but also the efficiency of the segmentation algorithm. The experiments show that the proposed algorithm could extract the contour of the breast tumor from the ultrasound images efficiently and accurately, which is fundamentally important for the following target feature extraction and analysis.