Comprehensive thyroid nodule prediction method and system and medium

Abstract

The invention relates to a comprehensive thyroid nodule prediction method and system and a medium, and belongs to the technical field of information prediction, and the method comprises the steps: obtaining an analog signal transmitted by an ultrasonic probe, and converting the analog signal into digital image information; performing primary data processing on the digital image information to obtain single-frame prediction vector information; performing secondary data processing based on the single-frame prediction vector to obtain prediction result information, and judging whether a thyroid nodule exists in the prediction result information; if the prediction result information exists, establishing a risk assessment model, and importing the prediction result information into the risk assessment model for risk assessment to obtain a risk assessment result report; and performing tracking processing on the risk assessment result report, judging whether the risk assessment result exceeds a preset risk assessment result, and if yes, sending out early warning information.

Description

technical field [0001] The present invention relates to the technical field of information prediction, in particular to a comprehensive thyroid nodule prediction method, system and medium. Background technique [0002] In recent years, with the rapid development of computer technology, some clinical radiologists have used AI technology based on ultrasound images to assist in the diagnosis of benign and malignant thyroid nodules, and have achieved classification performance comparable to imaging experts. However, this diagnostic technique judges benign and malignant nodules as a unit, and cannot judge benign and malignant nodules based on the patient as a whole. Not only that, but the performance of this diagnostic technique depends on the quality of image acquisition, which requires high experience of radiologists. However, using the existing clinical assessment methods, doctors need to input patient data and perform manual or automatic calculations every time a doctor perf...

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Problems solved by technology

Moreover, the user cannot scan the affected part anytime and anywhere, so that the affected part cannot be detected on the spot in real time.

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