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Convolutional neural network for discriminating nasopharyngeal carcinoma and benign hyperplasia on MRI.

Lun M WongAnn D KingQi Yong H AiW K Jacky LamDarren M C PoonBrigette B Y MaK C Allen ChanFrankie K F Mo
Published in: European radiology (2020)
• The convolutional neural network (CNN)-based algorithm could automatically discriminate between malignant and benign diseases using T2-weighted fat-suppressed MR images. • The CNN-based algorithm had an accuracy of 91.5% with an area under the receiver operator characteristic curve of 0.96 for discriminating early-stage T1 nasopharyngeal carcinoma from benign hyperplasia. • The CNN-based algorithm had a sensitivity of 92.4% and specificity of 90.6% for detecting early-stage nasopharyngeal carcinoma.
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