Method for obtaining fetal four-cavity tangent plane cardiac cycle video based on hybrid convolutional network

Abstract

The invention discloses a method for obtaining a fetal ultrasound four-cavity tangent plane cardiac cycle video based on a hybrid convolutional network. A complete period of the fetal four-cavity heart is defined as a period from the end of four-cavity tangent plane contraction to the end of next four-cavity tangent plane contraction, or a period from the end of four-cavity tangent plane relaxation to the end of next four-cavity tangent plane relaxation, and other intermediate periods are included in the period; wherein a video is used as input data; an image sequence after down-sampling is used as model input; features of time and space are extracted through a 3D convolutional network. By extracting 2D convolution network enhanced spatial dependence features, the features are fused. Finally, the classification probability and category of the next frame are predicted as three categories. A fetal four-cavity tangent plane cardiac cycle video which is complete and obvious in features iscounted through the joint probability under the condition that the category conforms to the complete cycle. The technical problem that an existing fetal heart detection method is difficult to guarantee the detection accuracy is solved.

Description

technical field [0001] The invention belongs to the field of fetal prenatal auxiliary diagnosis, and more specifically relates to a method for obtaining fetal four-chamber cardiac cycle video based on a hybrid convolutional network. Background technique [0002] Heart disease such as fetal heart dysplasia and heart malformation is one of the important causes of fetal birth defects or death. In view of this, it is very important to detect the heart of the fetus. [0003] At present, manual methods are mainly used for fetal heart detection, that is, the sonographer observes the four-chamber cardiac view of the fetal ultrasound video, and finds out the end-systole of the four-chamber cardiac view and the end-diastole of the four-chamber cardiac view, so as to determine the fetal four-chamber cardiac view. According to the four-chamber view cycle, the fetal heart development is diagnosed. [0004] However, the existing artificial fetal heart detection methods have some defects ...

AI Technical Summary

Problems solved by technology

[0005] In view of the above defects or improvement needs of the prior art, the present invention provides a method based on hybrid convolution network to obtain cardiac cycle video of fetal four-chamber heart view, the purpose of which is to solve the detection workload existing in the existing fetal heart detection method Large, difficult to operate, extremely demanding on the experience and professionalism of sonographers, difficult to guarantee the technical problems of detection accuracy, and the technical problems of considerable storage resources due to the need to collect a large amount of video data

Images