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Dysphagia has a large impact on individual patients and the society. However, the whole mechanism has not been analyzed. In order to understand dysphagia, it is essential to describe the anatomical features of cervical structures during swallowing. This study aims to segment cervical intervertebral disks (IDs) in videofluorography (VF) by multi channelization (MC) and convolutional neural network (CNN). The frame images of VF are gray-scale images. In the MC process, feature images are generated by applying image filters, such as the sobel filter and morphological tophat transform filter, to the frame images of VF. Among the feature images, three images are selected, and then color images are generated by setting the selected images to the RGB channels of the color images. The color images are input into CNN for segmentation. The proposed method is applied to actual VF, and experimental results are shown.

Preliminary Study on Intervertebral Disk Segmentation from Videofluorography by Multi Channelization and CNN