The effect of different oral imaging devices on auto-diagnosis: SLR camera vs fluorescence imaging

Abstract

Although deep learning has made remarkable achievements in medical image diagnosis, with accuracy exceeding that of medical specialists in some fields, those medical images are all formatted with specific imaging equipment and methods. In the field of oral surgery, the most popular images are with various single-lens reflex cameras no-standardized in terms of shooting range, angle, conditions, light intensity, number of pixels, etc. Since they are much noisier than the well-formatted medical images, it is more difficult to improve the diagnostic accuracy. In this research, we verified the influence of the shooting equipment, and examined the difference in accuracy when we used 1,000 images with a single-lens reflex camera 1,000 fluorescence images taken with a fluorescence observation equipment, respectively, and trained them with a model using CNN. We used 1,000 images taken with a single-lens reflex camera and 1,000 images with fluorescence observation equipment.