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This study proposes a set of novel feature vectors for accurate differentiation of 3 typical types of liver space-occupying lesions in ultrasound images. Experiments were performed on 280 cases of liver images, including 112 cases of normal liver images, 90 cases of liver cancer images, 38 cases of liver hemangioma images and 40 cases of liver cyst images. First, we defined two types of region of...
A computerized classification of breast tumor based on B-mode ultrasound and color Doppler flow imaging is proposed. First, the boundary of the breast tumor was manually delineated. Second, five contour features and two gray level features of the tumors were extracted from the B-mode ultrasonic images. Third, an optimal feature vector was created using K-means cluster algorithm. Then a back propagation...
Local histogram equalization (LHE) has been widely used in image enhancement. In medical ultrasound image the region of interest usually surrounds by large area of dark background, which contains little information but consume lots of computational resource. Direct application of LHE will not only be time-consuming but also affect the global visibility due to background distortion. Based on the characteristics...
In this paper, a hybrid method for the segmentation of medical ultrasound images is proposed. The method is composed of two parts as region growing and region merging. First, we initially segment the images into many small regions using a region growing method. The region growing algorithm is based on some pixels we specially choose as growing centers. The initially segmented images acquired from...
Traditionally, the gradient magnitude of an image pixel was the only feature in various image edge detection methods. However, this feature does not have good performance in noisy and low-contrast conditions, such as medical ultrasound images. A new edge detection feature, based on two brightness change direction angles difference (DAD) of one pixel in two different calculation methods, is proposed...
Breast cancer is one of the most common cancer in women. A novel method is presented in this paper for classification of the breast tumors as benign or malignant. The method combines k-means classification and a multilayer perception network with error back-propagation (BP) algorithm. The k-means which is an unsupervised classification method is used to get the cluster centers and select the training...
A method has been developed to quantitatively analyze sinoatrial nodes (SAN) using Doppler tissue images (DTI). Doppler tissue images of SAN are acquired using an intracardiac catheter via the superior vena cava in an in vivo experiment. A sequence of DTI images of a SAN is obtained, and a complete cycle of the SAN excitation is observed. The tissue acceleration of the SAN is extracted and quantitatively...
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