Benign hyperplasia is a common finding in the adenoid and walls of the nasopharynx and may hamper the detection of early-stage nasopharyngeal carcinoma (NPC) on MRI. In this study we aim to utilize deep learning to discriminate early-stage NPC from benign hyperplasia using T2-weighted-fat-suppressed MR images. We tested our method on a dataset of 413 cases, comprising 203 with early-stage NPC confined to the nasopharynx and 210 with benign hyperplasia. After training with validation (n=350 and n=13 respectively) followed by testing (n=50), the network achieved a promising result with a sensitivity of 100% and specificity of 83% for NPC detection.
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