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Automatic segmentation of the Epicardium and Endocardium plays an important role in the diagnosis of myocardial ischemia. Due to the speckle noise of ultrasound images and the complexity of cardiac tissue, the segmentation is still manual or semi-automatic. A fully automatic segmentation method based on Convolutional Neural Network (CNN) is proposed in this paper: localization segmentation method,...
A novel method based on Time-Frequency correction was presented to extract motor imagery feature from brain signal. The 2b datasets of BCI competition IV were used in this paper. Time-frequency features of right and left hand motor imagery were extracted from train datasets, respectively. The frequency band and time segment were selected based on frequency and time correction. The features were extracted...
Artery intima-media thickness (IMT) is a useful marker for diagnosis of atherosclerosis. In this paper, we have proposed a new scheme for detection and measurement of the IMT in medical ultrasound images, in which the image empirical mode decomposition (IEMD) is used as the detection part as well as adaptive gray stretching, and watershed segmentation for extracting boundary of intima. To measure...
In apple harvesting robot stereo vision system, fruit recognition based on least squares support vector machine (LS-SVM) and calibration based on binocular vision are proposed, in order to gain the location information of apples including depth. Firstly, vector median filtering, opening and closing operations are employed, then feature vectors, H and S components in HIS color model and shape features,...
In the robot vision system of the apple harvesting robot, the key is to recognize and locate the apple. To solve recognition questions such as high error rate, too much calculation and time consuming, a new recognizing method, support vector machine (SVM) is applied to improve recognition accuracy and efficiency. At first, vector median filter is used to remove the color images noise of apple fruit...
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