Nodule grading system and method based on thyroid ultrasound image

A technology of ultrasound image and classification method, which is applied in the fields of still image data clustering/classification, medical image, still image data retrieval, etc., can solve the problem of low accuracy rate

Pending Publication Date: 2021-06-08
北京小白世纪网络科技有限公司
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Problems solved by technology

[0005] The purpose of the present invention is to provide a nodule grading system and method based on thyroid ultrasound images, the nodule grading system can solve the problem of low accuracy in the process of automatic identification of thyroid nodules and nodule grading in the prior art

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  • Nodule grading system and method based on thyroid ultrasound image
  • Nodule grading system and method based on thyroid ultrasound image
  • Nodule grading system and method based on thyroid ultrasound image

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Embodiment Construction

[0052]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.

[0053] Such as figure 1 As shown, the present invention provides a method for grading nodules based on thyroid ultrasound images, the method specifically comprising:

[0054] S101, data preparation;

[0055] In this step, the first thyroid ultrasound image similar to the actual application scene is selected to form the first database, and the first database is processed to form a second database suitable for deep model processing; data preparation refers to, will be used for training The first database is processed into...

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Abstract

The invention provides a nodule grading system and method based on thyroid ultrasound images. The method comprises the steps: processing a first database to form a second database suitable for depth model processing; removing unreasonable second thyroid ultrasound images in the second database to form a third database; performing targeted modification on the third thyroid ultrasound image in the third database to form a fourth database; preprocessing a fourth thyroid ultrasound image in the fourth database to form a fifth database; extracting a part of fifth thyroid ultrasound images in the fifth database to form a training database; and through the trained model structure, performing nodule detection on the thyroid ultrasound image in an actual application scene to obtain a nodule grade. The nodule grading system based on the thyroid ultrasound image solves the problem of low accuracy in the thyroid nodule automatic identification and nodule grading process in the prior art.

Description

technical field [0001] The present invention relates to the technical field of computer artificial intelligence deep learning, in particular to a nodule grading system and method based on thyroid ultrasound images. Background technique [0002] The automatic recognition of thyroid cancer by traditional machine learning methods is often divided into two steps, first extracting features, and then using a classifier for classification. Commonly used feature extraction methods include SIFT, HOG, Haar-like, LBP features, etc. The quality of the extracted features determines the effect of automatic recognition; feature extraction requires constant parameter adjustment, which is a time-consuming and labor-intensive task. There is a great correlation, and experienced experts often extract more useful features, but there are not many technical personnel with such richness. Commonly used classifiers include SVM, decision tree, logistic regression, etc. Different classifiers have diff...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/70G16H30/20G06F16/51G06F16/55G06F16/583G06K9/34G06K9/62
CPCG16H50/70G16H30/20G06F16/51G06F16/55G06F16/583G06V10/267G06V2201/032G06F18/285
Inventor 杜强王晓勇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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