Thyroid nodule echo analysis device

Abstract

The invention relates to a thyroid nodule echo analysis device. The thyroid nodule echo analysis device comprises an image acquisition module which is used for acquiring an ultrasonic image with a thyroid nodule; a nodule-of-interest image extraction module which is used for obtaining a nodule-of-interest image according to the ultrasonic image; a thyroid nodule gland detection module which is used for obtaining gland reference according to the ultrasonic image; a detection area generation module which is used for generating a first detection area and a second detection area based on the ultrasonic image; a thyroid muscle and fascia detection module which is used for obtaining muscle and fascia reference according to the first detection area; a thyroid trachea and blood vessel detection module which is used for obtaining a trachea and blood vessel reference according to the second detection area; and a thyroid nodule echo detection module which is used for detecting nodule echo according to the gland reference, the muscle and fascia reference and the trachea and blood vessel reference. The thyroid nodule echo detection method can effectively detect the thyroid nodule echo.

Description

technical field [0001] The invention relates to the technical field of auxiliary medical diagnosis, in particular to an echo analysis device for thyroid nodules. Background technique [0002] Thyroid cancer is one of the most common cancers in women worldwide, with women three times more likely than men. In 2018, one in 20 cancers diagnosed in women was thyroid cancer. Ultrasound imaging is a non-invasive, radiation-free, and low-cost tumor diagnostic technique. However, identifying thyroid nodules and detecting tumor signs from ultrasound images is a challenging task due to the low quality of ultrasound images. [0003] In general, the growth and development of a malignant tumor can be reflected by its shape, appearance, texture, composition, and many other factors. As an effective tool, gray-scale ultrasound (US) images can visualize these factors, helping doctors to better observe and understand the performance of pathological sites. However, in current clinical pract...

AI Technical Summary

Problems solved by technology

However, in current clinical practice, the reading of ultrasound image features largely depends on the subjective or semi-subjective analysis of images by sonographers, which limits the wide application of ultrasound.

However, there are no studies on quantitative feature analysis of TI-RADS to improve the diagnostic performance of thyroid cancer classification.

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