Shantou Institute of Ultrasonic Instruments Co., Ltd.

Jingfeng Guo

Liexiang Fan

Zhonghong Wu

Bin Li

Delai Li

Yu Wang

Yijie Chen

Shaohui Chen

Zehang Cai

Jinhao Lin

Weiwu Chen

Zichun Chen

Jinyao Yang

Xiaoming Zhou

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

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

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Shantou, China

Jingfeng Guo