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Thyroid nodule edge sign classification method, device and system

A technology of thyroid nodules and classification methods, applied in the field of deep learning, can solve the problems of complex ultrasound images of the thyroid gland, increase the entry threshold of practitioners and researchers and the complexity of operations, so as to improve the effect and avoid puncture surgery Effect

Pending Publication Date: 2021-09-24
北京小白世纪网络科技有限公司
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  • Application Information

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Problems solved by technology

[0002] Thyroid ultrasound images are complex, and the ultrasound features of benign and malignant nodules have many similarities, which invisibly increases the entry threshold and operational complexity for practitioners and researchers in this field

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Embodiment Construction

[0021] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of this application.

[0022] Thyroid nodules are a common condition, especially in women. According to different examination methods, the incidence of thyroid nodules ranges from 19% to 68%. Among patients with thyroid nodules, about 10% have the risk of malignant tumors. The incidence rate of thyroid cancer is 8.28 / million, and it continues to grow at a rate of 5% per year. Amo...

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Abstract

The embodiment of the invention provides a thyroid nodule edge sign classification method, device and system. The method comprises the following steps: acquiring a thyroid ultrasound image training set; constructing a convolutional neural network model; taking a thyroid ultrasound image in the training set as the input of the convolutional neural network model, taking a classification result as the output of the convolutional neural network model, and training the convolutional neural network model; classifying thyroid nodule edge signs in the thyroid ultrasound image to be processed according to the convolutional neural network model. According to the thyroid nodule edge sign classification method and device, a doctor can be assisted in completing classification of thyroid nodule edge signs, unnecessary puncture operations caused by TI-RADS grading errors due to inaccurate edge sign classification are avoided, and body, money and spirit burdens of a patient are relieved.

Description

technical field [0001] The embodiments of the present application relate to the field of deep learning technology, and in particular to a method, device and system for classifying thyroid nodule margin signs. Background technique [0002] Thyroid ultrasound images are complex, and the ultrasound features of benign and malignant nodules have many similarities, which invisibly increases the entry threshold and operational complexity for practitioners and researchers in this field. In order to solve the problems caused by this non-standardized process, the standardization of thyroid grading was proposed by Horvath in his paper in 2009. The assessment system is called TI-RADS (Thyroid Imaging Reporting and Data System), which aims to simplify classification and reduce grading. difficulty. With the passage of time, more people participated in the formulation and improvement of this standard, and TI-RADS has gradually matured and become the industry-recognized thyroid grading sta...

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Application Information

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IPC IPC(8): G06T7/00G06T7/13G06T5/00G06K9/62G06N3/04G06N3/08
CPCG06T7/0012G06T7/13G06N3/08G06T2207/10132G06T2207/20081G06T2207/20084G06T2207/30004G06N3/045G06F18/241G06F18/214G06T5/70
Inventor 杜强严亚飞王晓勇牟晓勇聂方兴
Owner 北京小白世纪网络科技有限公司
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