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To improve the accuracy and sensitivity of the breast tumor classification based on ultrasound images, a computer-aided classification algorithm is proposed using the Affinity Propagation (AP) clustering. Five morphologic features and three texture features are extracted from each breast ultrasound image. The AP clustering with an empirical value of "preference" is used as the primary classification...
According to texture analysis in low frequency sub-band of DWT, an adaptive image hiding algorithm is proposed. The low-frequency part of DWT is classified as smooth, edge and texture region by entropy and standard deviation, and different regions are assigned with different hiding bits, which will increase the hiding capacity. The blind detection is accomplished by resetting low bits in DWT low-frequency...
A computerized classification based on morphologic and texture features is proposed to increase the accuracy of the ultrasonic diagnosis of breast tumors. Firstly, tumor boundaries are obtained with the gray-level threshold segmentation algorithm and the dynamic programming method. Then five morphologic features and two texture features are extracted. Finally, an artificial neural network with the...
Based on VOXEL-MAN software and our previous work on merging acupoint information with the dataset of the male Visible Human, we have refined the segmentation method for muscles and visualized the anatomical structure of meridians. In interactive segmentation, we obtain additional information on connectivity and texture. We also apply surface fitting to track muscle contours on data slices where the...
The classification of the uterine myoma and adenomyosis from their ultrasound images mainly depends on doctors' experience and lacks objective criterions. Here a novel classification method is proposed using the multiresolution analysis and the orientational fractal analysis. Firstly, texture features under various resolutions and orientational fractal features are obtained from ultrasound images...
Feature extraction techniques in the ultrasonic images of a liver were studied firstly. As an initial result, total 25 parameters relating to cirrhosis were extracted. They were obtained from the motion curve of the liver in an M-mode image, and from the texture using a B-mode image. Then the efficiency of every parameter was analyzed, and with the use of a feature fusion method a set of 20 useful...
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