Shantou Institute of Ultrasonic Instruments Co., Ltd.

Liexiang Fan

Bin Li

Zhonghong Wu

Delai Li

Yu Wang

Jingfeng Guo

Shaohui Chen

Peifeng Chen

Jinhao Lin

Zichun Chen

Jinyao Yang

Haomiao Qiu

Shutian Su

Yijie Chen

Xurui Zeng

Zehang Cai

Yinan Huang

Yuqiang Kang

Zhongyun Wei

Weiwu Chen

Xiaoming Zhou

An automatic myocardial segmentation method in two-dimensional echocardiography includes: calculating and extracting ridge information in two-dimensional echocardiography; extracting image skeleton data, and connecting fragmented skeleton data to obtain continuous skeleton data by using interpolation; screening the continuous skeleton data, and extracting two optimal paths from a top to a bottom based on a myocardial feature to obtain left and right myocardial skeletons; extracting a set of feature point candidates from the left and right myocardial skeletons, and selecting a pair of key matching feature points from the set of feature point candidates as anchor points based on the myocardial feature; entering anchor point data and left and right myocardial skeleton data in a mathematical model of heart chambers to fit the morphology of heart chambers and obtain an initial myocardial contour; and constructing a myocardial feature energy equation.

Automatic myocardial segmentation method in two-dimensional echocardiography

Disclosed are a convex-linear bi-plane probe and its application method in prostate volume calculation. The present invention adopts the following technical solution: comprising a probe housing and a probe assembly contained in the probe housing, the probe assembly comprising a linear probe and a convex probe contained at the end of the linear probe, with the linear element inside the linear probe and the convex element inside the convex probe connected as one piece. The benefits of the present invention are that: by setting a convex probe at the end of the linear probe, and by connecting the linear element and the convex element as one, the volume of the probe can be significantly reduced. Furthermore, the use of convex-linear biplane probe and its integrated design collect two orthogonal ultrasound images of the prostate, which improves the accuracy of prostate volume calculation.

Convex-linear bi-plane probe and its application method in prostate volume calculation

The present disclosure relates to the field of ultrasonic detection, in particular to a craniocerebral ultrasonic standard plane imaging and automatic detection and display method for abnormal regions. The following technical solution is adopted: contour detection is performed on the scanned ultrasound images the skull to construct a skull surface model, and the standard planes in ultrasound images are identified and extracted according to the skull surface model. The symmetry of the standard planes in ultrasound images is used to compare the similarity, so as to obtain the abnormal regions for segmentation and display. The advantages of the present disclosure are as follows: the skull surface model is constructed by detecting the cranial edge, and the coordinate system is established based on this model, thereby the standard planes in ultrasound images can be quickly identified from the scanned ultrasound images.

Cranial ultrasonic standard plane imaging and automatic detection and display method for abnormal regions

A first-order estimation method of shear wave velocity, includes the steps of demodulating entry data, and obtaining a complex angle value, matrix average, offset matrix, displacement matrix and shear wave velocity. According to the method, the main contour of the displacement curve is extracted by the quadrature decomposition of matrix, thereby improving the signal quality of the shear wave estimation. Unlike conventional method which needs estimating twice, the shear wave displacement curve can be estimated directly to reduce estimation errors and improve estimation efficiency.

First-order estimation method of shear wave velocity

The disclosure provides a multi-target 3D ultrasound image segmentation method based on simulated and measured data. The method includes: presetting conventional acoustic parameters; collecting raw 3D data; employing an initial segmentation algorithm to segment the raw 3D data; substituting with the conventional acoustic parameters according to probability in order to form a transitional image model; performing a simulation operation; performing transformation to obtain simulated data; performing a comparison operation; adjusting corresponding magnitude of the probability in each probability variable, and returning to the step of substituting with the conventional acoustic parameters. According to the probability, the conventional acoustic parameters are substituted into a model of an incomplete target tissue, the simulation operation is then performed, the probability is adjusted, and repeatedly, corrections are performed continuously in an iterative convergence manner till each incomplete target tissue is completely substituted by a certain normal tissue or lesion tissue.

Simulated and measured data-based multi-target three-dimensional ultrasound image segmentation method

Growing community of inventors

Shantou, China

Liexiang Fan