Abstract
Swallowing is achieved by a sequence of actions performed by cervical structures. Although a lot of patients suffer from dysphagia in the world, the mechanism and kinematics of swallowing are not elucidated sufficiently. This study aims to segment intervertebral disks (IDs), which are ones of representative cervical structures, in videofluorographic (VF) images by use of convolutional neural network (CNN). The proposed method consists of three steps: extraction of cervical masks, CNN-based segmentation of candidate regions of IDs, and the elimination of false positives. This segmentation method was applied to actual VF images of eleven participants that have fifty-one not-occluded IDs, and forty-three IDs were segmented successfully.
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