An image classification method and device for predicting far-end metastasis of head and neck cancer
A technology of metastasis prediction and classification method, applied in medical images, computer components, instruments, etc., can solve the problem of fewer head and neck cancers, and achieve the effect of avoiding pain
Inactive Publication Date: 2019-06-28
GUILIN UNIV OF ELECTRONIC TECH
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Problems solved by technology
Deep learning has achieved remarkable results in natural image classification. Currently, there have been studies applying deep learning to medical image processing and diagnosis. However, there are few imaging data of head and neck cancer. So far, no one has applied deep learning to Distant Metastasis Prediction in Head and Neck Cancer
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[0037] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, in the case of no conflict, the following embodiments and features in the embodiments can be combined with each other.
[0038] It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic ideas of the present invention, and only the components related to the present invention are shown in the diagrams rather than the number, shape and shape of the compo...
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The invention provides an image classification method for predicting far-end metastasis of head and neck cancer, which comprises the following steps: acquiring medical image data including lung CT data and head and neck CT data; Preprocessing the medical image data; Constructing a first classifier model and a second classifier model according to the preprocessed medical image data, wherein the first classifier model is an image omics classifier based on a convolutional neural network, the second classifier model is a classifier based on feature engineering image omics, and the third classifieris a classifier based on clinical information; Integrating the first classifier model, the second classifier model and the third classifier model through a weighted average method to form a final classification model; and inputting medical images and clinical information into the final classification model, and classifying the medical images.
Description
technical field [0001] The invention relates to the field of image classification, in particular to an image classification method and device for predicting distant metastasis of head and neck cancer. Background technique [0002] Malignant tumors of the head and neck account for about 5% of malignant tumors in the whole body, and the vast majority of pathological types are squamous cell carcinomas. Due to the complex anatomical structure and other reasons of head and neck squamous cell carcinoma, although surgery is the main method of treatment, the rate of radical resection is low, and the early clinical symptoms are hidden, and most of the patients are in the middle and late stages of tumor when they see a doctor, so it has always been the first choice in tumor treatment. difficulty. The diagnosis of head and neck squamous cell carcinoma usually requires a combination of medical history, signs, endoscopic biopsy and related imaging examinations. Imaging examinations are ...
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Login to View More IPC IPC(8): G06K9/62G16H30/40G06N3/04
Inventor 胡聪王鹏朱望纯周甜许川佩朱爱军万春霆陈涛
Owner GUILIN UNIV OF ELECTRONIC TECH