Migration learning lung lesion tissue detection system based on MaskScoring R-CNN network

Abstract

A migration learning lung lesion tissue detection system based on an MaskScoring R-CNN network comprises a storage module for storing four lung diseases including lung cancer, pneumonia, pulmonary tuberculosis and emphysema and further comprises a diagnosis module, and the diagnosis module is in communication connection with the storage module and comprises the following steps of 1) preprocessinga medical image; 2) constructing the MaskScoring R-CNN network model, wherein the step 2) specially comprises 1, constructing a shared convolutional neural network backbone (for feature extraction); 2, carrying out transfer learning on a shared convolutional neural network; 3, constructing an FPN network; 4, constructing an RPN network; 5, constructing an ROIAlign layer; 6, adding the MaskIoU head; and 3) identifying the lung medical image lesion tissue, inputting a to-be-detected lung CT image into the constructed MaskScoring R-CNN network, outputting and obtaining an identified image by thenetwork, framing out and masking the identified lesion tissues, and marking the lesion categories. According to the method, the requirement for high precision of medical image segmentation is met, andthe network can have the good generalization.

Description

technical field [0001] The invention relates to a detection system for lung lesions. [0002] technical background [0003] For nearly half a century, the incidence and mortality of lung cancer have been rising continuously, doubling in 15 years. The incidence of lung cancer in industrially developed areas is high, and the more you smoke, the higher the incidence. There is an obvious dose relationship. Both mortality and mortality rank first in malignant tumors. In order to be able to detect early and give timely treatment in the early stage of lung lesions, accurate lesion detection methods are extremely critical. [0004] Common lung diseases include lung abscess, emphysema, tuberculosis, pulmonary nodules, etc. In medicine, chest X-ray examination is one of the necessary basic examination items for lung diseases, which is helpful for the diagnosis of lung inflammation, atelectasis, emphysema, pneumothorax, pleural effusion and other diseases. Chest CT examination is hel...

AI Technical Summary

Problems solved by technology

In the present invention, the MaskScoring R-CNN neural network used for semantic segmentation of natural images can be applied to medical image segmentation to solve the problem of lung pathological tissue segmentation

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