Thyroid nodule TI-RADS grading system and method

A technology of TI-RADS, classification method, applied in image analysis, image data processing, instruments, etc., can solve the problem of poor automatic classification effect and so on

Pending Publication Date: 2021-05-18
北京小白世纪网络科技有限公司
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Problems solved by technology

[0004] The purpose of the present invention is to provide a TI-RADS grading system and method for thyroid nodules, which can solve the problem of poor automatic classification of thyroid nodules by five factors in the prior art

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  • Thyroid nodule TI-RADS grading system and method
  • Thyroid nodule TI-RADS grading system and method

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Embodiment Construction

[0036] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0037] Such as figure 1 Shown, a kind of thyroid nodule TI-RADS grading method, described method specifically comprises:

[0038] S101, data noise reduction;

[0039] In this step, noise reduction is performed on the first image data set by applying an image morphology method; noise reduction is performed on the first image data set. Since the first thyroid ultrasound image contains information such as instrument model, date, and scale line, which has a great impact on the image feature extraction and recognition effec...

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Abstract

The invention provides a thyroid nodule TI-RADS grading system and method. Comprising the following steps: denoising a first image data set by applying an image morphological method; performing data enhancement on the first image data set to form a second image data set; training the deep learning network group to form a corresponding first model group; improving the recognition effect of the trained first model group through a domain adaptation method; fusing the first model group through parameter search to obtain a second model. According to the thyroid nodule TI-RADS grading system, the problem of poor automatic classification effect of five factors of thyroid nodules in the prior art is solved.

Description

technical field [0001] The invention relates to the technical field of deep learning of computer artificial intelligence, in particular to a TI-RADS grading system and method for thyroid nodules. Background technique [0002] Thyroid nodules are very common in ultrasound diagnosis, and most of them are benign, and do not require intervention treatment, but a small number of benign nodules may gradually become malignant, and eventually evolve into tumors or indirectly cause cancer, so it is necessary to pass some assistance Diagnostic methods perform nodule detection and correct classification as much as possible. In the early stage of thyroid nodule detection, because the ultrasound images of thyroid nodules are very complex and diverse, the diagnosis methods for benign and malignant thyroid nodules are also very diverse. Different institutions and experts have developed their own detection methods and judgment standards based on their own experience. It directly complicate...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T5/00G06K9/62G06N3/04
CPCG06T7/0012G06T5/002G06T2207/10132G06N3/045G06F18/214
Inventor 杜强严亚飞王伟刘贻豪佟文娟郭雨晨聂方兴唐超
Owner 北京小白世纪网络科技有限公司
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