A method and device for automatically identifying primary tumors of nasopharyngeal carcinoma

Abstract

The present invention relates to the field of image processing, and provides a method and device for automatically identifying primary tumors of nasopharyngeal carcinoma. The method includes using the ResNeXt152 network as the backbone network in the Mask RCNN deep semantic segmentation network, and defining the prediction category of the semantic segmentation branch. There are three types; the deep semantic segmentation network is trained by using multiple preprocessed MRI 3D images, and its output includes: the pixel position information of the four endpoints of the rectangular frame containing the tumor area, the probability that the rectangular frame is a tumor area, and the rectangular frame The probability that each pixel in the frame belongs to the primary tumor area; the MRI 3D image to be identified is input into the deep semantic segmentation network to obtain the probability that each pixel belongs to the primary tumor area; the method uses the deep learning method and uses Mask RCNN Network architecture and its improvement can effectively improve the accuracy of prediction and the generalization ability of the model.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method and device for automatically identifying primary tumors of nasopharyngeal carcinoma. Background technique [0002] In the medical field, IMRT technology can greatly improve the survival rate and quality of life of cancer patients. However, this advanced treatment method requires accurate judgment of the contour of the target tumor, and the development of radiation treatment plan can take hours of radiologists. [0003] Because rhinitis is adjacent to the skull base, 60%-70% of patients experience skull base bone destruction at the time of treatment, and 18% of patients even have intracranial and / or cavernous sinus violations, making surgery difficult. At the same time, 85% of patients are accompanied by metastasis of neck or throat lymph nodes, which are not suitable for surgery. The World Health Organization divides nasopharyngeal carcinoma into three types: ...

AI Technical Summary

Problems solved by technology

[0005] Embodiments of the present invention provide a method and device for automatically identifying primary tumors of nasopharyngeal carcinoma, to solve the problem of low accuracy in identifying primary tumors in the prior art

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