Thyroid ultrasonic image automatic identification system based on depth neural network, computer equipment, storage medium

Abstract

The invention discloses a thyroid ultrasonic image automatic identification system based on a depth neural network, belonging to the technical field of image identification. The system comprises a depth neural network model comprising an end-to-end neural network based on yolov2, the detection network comprising a convolution layer, a pooling layer, a full connection layer and an output layer; Thedepth neural network model further comprises a depth residual network comprising a convolution layer, a pooling layer, a full connection layer and an output layer, the last pooling layer and the fullconnection layer are removed, and the depth residual network and the detection network share a first convolution layer and the last pooling layer and the full connection layer. This embodiment uses computer technology to process thyroid ultrasound images instead of doctors to complete the tracking and identification of pathological tissues, can reduce manual operation, has consistent processing results and considerable accuracy, and is convenient for integrated and large-scale application.

Description

technical field [0001] The present invention relates to the technical field of image recognition, in particular to an automatic recognition system for thyroid ultrasound images based on a deep neural network, computer equipment, and a storage medium. Background technique [0002] Thyroid cancer is the most common malignant tumor among endocrine system tumors, and its incidence is increasing year by year. Ultrasound examination is the preferred method for diagnosing thyroid nodules. Ultrasound and FNAB examinations are most commonly used to distinguish benign and malignant thyroid nodules. For thyroid nodules that exist or are suspected to exist or are incidentally discovered by other imaging examinations, thyroid ultrasonography should be actively performed. examine. [0003] In traditional diagnosis, the interpretation of ultrasound results mainly relies on the knowledge and experience of sonographers, which is highly subjective. With the sharp increase in the number of p...

AI Technical Summary

Problems solved by technology

Thyroid computer aided diagnosis system (computer aided diagnosis, CAD) has achieved rapid development, which can effectively reduce errors caused by subjective factors and assist doctors to make a fast and accurate diagnosis. Realize automatic identification

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