Thyroid CT image nodule automatic diagnosis system based on neural network

Abstract

The invention discloses a thyroid CT image nodule automatic diagnosis system based on a neural network, and the system sequentially comprises: an image preprocessing module, which carries out the preprocessing of an original thyroid CT image, and carries out the marking of nodule information of the preprocessed image; a image data enhancement module, which is used for expanding the thyroid CT image data set; a nodule semantic segmentation module, which is used for carrying out image semantic segmentation through a neural network to segment nodule parts; an image algorithm optimization module, which enables the output of the semantic segmentation network to be in smooth transition and adapted to the classification network; and a classification prediction module, which is used for carrying out benign and malignant classification judgment on each segmented thyroid nodule by using a hybrid network model. According to the system, end-to-end thyroid nodule diagnosis can be realized, additional image processing and data labeling work on CT images are not needed, and high-accuracy and high-efficiency thyroid nodule automatic identification and benign and malignant classification can be realized.

Description

technical field [0001] The invention relates to the field of medical image processing, in particular to a neural network-based automatic identification and classification system for benign and malignant thyroid glands. Background technique [0002] The thyroid gland is located right in front of the neck of the human body, below the Adam's apple, shaped like a butterfly, and is the largest endocrine gland in the human body. The thyroid has the function of secreting thyroid hormones, which play an important role in human growth and metabolism. Thyroid nodules are lumps of abnormal growth of thyroid cells. The American Thyroid Association defines a thyroid nodule as a discrete lesion on the thyroid gland. With the help of imaging examination, it can be observed that the nodule is different from the normal thyroid tissue structure and has a relative boundary. At the time of onset, there may be one or more thyroid nodules. The texture of the nodules may be solid or cystic. The ...

AI Technical Summary

Problems solved by technology

At present, the treatment of thyroid nodules at home and abroad mainly relies on ultrasound images, but ultrasound images have problems such as low clarity and little useful information.

X-ray computed tomography (CT) technology has become an imaging method widely used in the diagnosis and follow-up of thyroid nodules. However, traditional CT image discrimination requires doctors to read a large number of thyroid CT slice pictures, which cannot be quickly and effectively diagnosed. low efficiency

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