Diagnosis of Maxillary Sinusitis on Waters' View Conventional Radiograph using Convolutional Neural Network

Youngjune Kim, Kyong Joon Lee, Leonard Sunwoo, Dongjun Choi, Chang-Mo Nam, Jung Hyun Park

Abstract: We compared the diagnostic performance of convolutional neural network (CNN) in diagnosing maxillary sinusitis on Waters’ view radiograph with those of five radiologists using temporal and geographic external test sets. In the temporal external test set, area under the receiver operating characteristic curves (AUC) of CNN was 0.93, which was comparable with AUCs of radiologists which ranged 0.83–0.89. In the geographic external test set, AUC of CNN was 0.88, which was comparable with AUCs of the radiologists which ranged 0.75–0.84. The CNN can diagnose maxillary sinusitis on Waters’ view radiograph as accurately as the expert radiologists.

Author Affiliation: Seoul National University Bundang Hospital

Keywords: maxillary sinusitis, convolutional neural network (CNN), deep learning, comparison with radiologists, head and neck imaging