ABSTRACT
Deep learning has profoundly advanced many fields. In computer vision, this progress became feasible due to a combination of immense computing power, large data availability, and convolutional neural networks (CNNs). CNNs were a game-changer for computer vision because they efficiently process grid-like data and adapt the final model’s behavior according to the target. With these means, today’s researchers are now proposing tools and methods that were im- 171practicable and seemed unreal a decade ago. Many methods and tools were and are being proposed and developed in the medical imaging field. However, the deep learning applications in dentistry are still incipient, being an open-field for studies and researchers entering the field. This chapter offers a comprehensive discussion on the most common images used in dentistry and their deep learning literature applications, relating them to the corresponding computer vision task. We discuss promising avenues to the complex problem of automatic report generation. At the end of this chapter, we present an overview of the field’s achievements, opportunities, and challenges.
