Nasopharyngeal carcinoma distant metastasis predicting system based on deep learning algorithm
A technology of transfer prediction and deep learning, applied in computing, informatics, medical informatics, etc., can solve problems such as accurate judgment of prognosis information, and achieve the effect of improving final accuracy, reducing cost, and improving efficiency
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[0029] In the prediction of distant metastasis of nasopharyngeal carcinoma based on deep learning algorithm proposed by the present invention, the specific functions of each module are realized in the following ways:
[0030] The image acquisition module reads the digital images of pathological sections of nasopharyngeal carcinoma patients scanned completely (multiple ≥ 400 times, resolution ≥ 12000×12000), and manually or software analyzes the digital images of pathological sections of nasopharyngeal carcinoma patients The tumor cell area (resolution ≥ 1000×1000) is delineated, and a large number of digital images of nasopharyngeal carcinoma tumor pathological sections with known metastasis information stored in the acquisition module are used as the training set of the deep learning algorithm;
[0031] Image preprocessing module: cut the tumor area outlined in the image acquisition module, and use the gray threshold method and Otsu threshold method to filter the background of...
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