Abstract: An ultrasonic device and a method and system for transforming the display of a three-dimensional ultrasonic image thereof. The method comprises: first acquiring original ultrasonic three-dimensional body data including a tested object (S10); detecting the orientation of the tested object from the original ultrasonic three-dimensional body data according to image features of the tested object (S20); then comparing the orientation of the tested object with a desired orientation, so as to obtain a rotation transformation parameter in a three-dimensional coordinate system (S30); next, rotating and transforming the original ultrasonic three-dimensional body data according to the rotation transformation parameter, so as to obtain the transformed three-dimensional body data (S40); and finally, outputting the transformed three-dimensional body data (S50).

Abstract: The present disclosure relates to a method for ultrasound imaging and a related equipment, the method for ultrasound imaging comprising: obtaining ultrasound body data of a test object; determining position information of a target anatomical structure from the ultrasound body data; determining an ultrasound image of the target anatomical structure from the ultrasound body data according to the position information of the target anatomical structure; and displaying the ultrasound image.

Abstract: An ultrasonic device and a method and system for transforming the display of a three-dimensional ultrasonic image thereof. The method comprises: first acquiring original ultrasonic three-dimensional body data including a tested object (S10); detecting the orientation of the tested object from the original ultrasonic three-dimensional body data according to image features of the tested object (S20); then comparing the orientation of the tested object with a desired orientation, so as to obtain a rotation transformation parameter in a three-dimensional coordinate system (S30); next, rotating and transforming the original ultrasonic three-dimensional body data according to the rotation transformation parameter, so as to obtain the transformed three-dimensional body data (S40); and finally, outputting the transformed three-dimensional body data (S50).

Abstract: Systems and methods that facilitate image motion analysis are described herein. According to a first image motion analysis technique a first image is warped according to a locally affine model. The first warped image and a second image are compared and a match between the first warped image and the second image is discovered. A value for a motion parameter is estimated based on the match. According to a second image motion analysis technique, an image sequence is converted into an input matrix. A column of the input matrix corresponds to a vectorized image related to the image sequence. The input matrix is approximated with a low rank matrix having a lower rank than the input matrix. One or more outliers of the input matrix are detected.

Abstract: The subject disclosure relates to motion estimation and compensation of feature-motion decorrelation. In an aspect, coupled filtering can be employed to solve feature-motion decorrelation problems. In further aspects, a linear convolution model can be employed to model image variation caused by motion, and an image before motion and a warped image after motion can be filtered with a pair of filters having motion parameters shared with a tissue motion model. Compensation of feature-motion decorrelation in ultrasound images demonstrates various aspects of the subject disclosure.

Abstract: Systems and methods that facilitate image motion analysis are described herein. According to a first image motion analysis technique a first image is warped according to a locally affine model. The first warped image and a second image are compared and a pattern that matches between the first warped image and the second image is discovered. A value for a motion parameter is estimated based on the pattern. According to a second image motion analysis technique, an image sequence is converted into an input matrix. A column of the input matrix corresponds to a vectorized image related to the image sequence. The input matrix is approximated with a low rank matrix having a lower rank than the input matrix. One or more outliers of the low rank matrix are detected.

Abstract: The subject disclosure relates to motion estimation and compensation of feature-motion decorrelation. In an aspect, coupled filtering can be employed to solve feature-motion decorrelation problems. In further aspects, a linear convolution model can be employed to model image variation caused by motion, and an image before motion and a warped image after motion can be filtered with a pair of filters having motion parameters shared with a tissue motion model. Compensation of feature-motion decorrelation in ultrasound images demonstrates various aspects of the subject disclosure.