Three-dimensional ultrasonic abdominal hernia patch detection method and system based on deep learning

Abstract

The invention provides a three-dimensional ultrasonic abdominal hernia patch detection method and system based on deep learning, and relates to the technical field of image processing. The method comprises the following steps of: collecting a three-dimensional ultrasonic image through ABUS; extracting coronal plane data of the image and then carrying out data amplification; performing patch calibration and splitting on the amplified image data to obtain a data set, constructing and training a convolutional neural network through the data set to output prediction box information, selecting a patch candidate region according to the prediction box information, and screening out a final patch detection result from the patch candidate region through an NMS algorithm. According to the method, coronal plane extraction and data amplification processing are carried out on original image data, so that the recognition accuracy of the neural network is enhanced; according to the method, the generalization ability and robustness of the neural network are improved, the risk of fitting in the network training process is reduced, network structure parameters are adjusted, network training is accelerated, the network performance is improved, and the detection performance and accuracy are improved by adopting the NMS to perform clustering reconstruction.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method and system for detecting a three-dimensional ultrasonic abdominal hernia patch based on deep learning. Background technique [0002] With the rapid development of ultrasonic imaging technology and patch materials, traditional ultrasonic testing, such as hand-held ultrasound (HHUS), cannot completely and reliably identify the popular lightweight (LW) patches, while automated three-dimensional breast ultrasound (ABUS) ) is a relatively mature and innovative ultrasound imaging mode nowadays. Compared with two-dimensional ultrasound, it can provide higher diagnostic accuracy, better prediction of lesion size, more intuitive visualization of lesion area and the relationship between adjacent tissues, and has been successfully applied to The diagnosis of breast lesions has also attracted the attention of scholars in the diagnosis of abdominal wall hernia. However, the...

AI Technical Summary

Problems solved by technology

However, the amount of data generated by ABUS for each patient is huge, and manual review of image data is extremely time-consuming and manpower-intensive, and the interpretation of images by different operators is different, and it is very easy to miss the diagnosis of weak abnormal areas

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