Digital dental reconstruction can be a more efficient and effective mechanism for artificial crown construction and period inspection. However, optical methods cannot reconstruct those portions under gums, and X-ray-based methods have high radiation to limit their applied frequency. Optical coherence tomography (OCT) can harmlessly penetrate gums using low-coherence infrared rays, and thus, this work designs an OCT-based framework for dental reconstruction using optical rectification, fast Fourier transform, volumetric boundary detection, and Poisson surface reconstruction to overcome noisy imaging. Additionally, in order to operate in a patient's mouth, the caliber of the injector is small along with its short penetration depth and effective operation range, and thus, reconstruction requires multiple scans from various directions along with proper alignment. However, flat regions, such as the mesial side of front teeth, may not have enough features for alignment. As a result, we design a scanning order for different types of teeth starting from an area of abundant features for easier alignment while using gyros to track scanned postures for better initial orientations. It is important to provide immediate feedback for each scan, and thus, we accelerate the entire signal processing, boundary detection, and point-cloud alignment using Graphics Processing Units (GPUs) while streamlining the data transfer and GPU computations. Finally, our framework can successfully reconstruct three isolated teeth and a side of one living tooth with comparable precisions against the state-of-art method. Moreover, a user study also verifies the effectiveness of our interactive feedback for efficient and fast clinic scanning. available artificial intelligence technologies. Therefore, this work aims at developing a digital dental reconstruction framework based on harmless, gum-penetrative optical coherent tomography (OCT). There are various digital reconstruction methods. Optical reconstruction [1-4] uses cameras to capture visible light reflected from objects for reconstruction. Additionally, there are also light detection and ranging (LIDAR)systems [5] [6] [7] , which actively emit laser rays and reconstruct objects by stereoscopic matching or reflected time measurement. However, gums occlude part of teeth to limit their reconstruction ability. Furthermore, teeth having complex scattering properties make reconstruction more difficult. In order for volumetric reconstruction, computed tomography (CT) [8, 9] uses X rays to penetrate human tissues and to measure the absorption ratio, and magnetic resonance imaging (MRI) [10] uses various magnetic resonances to locate various tissues. However, because they target the whole torso and a tooth only occupies a small portion, the reconstruction may not have enough information for precision. Moreover, they are too noxious for periodic inspection and frequent reconstruction. Optical coherence tomography (OCT) [11, 12] can harmlessly penetrate gums using low-coherence infrared rays, but the process easily induces disturbances in its frequency-based reflections resulted in noisy capturing. There are OCT-based dental research for manually inspecting under-gum dental structures [13, 14] and periodontal inspection [15] [16] [17] . However, they do not aim at reconstructing the dental surface and requires manual inspection and examination. To the best of our knowledge, there is still no work applying the technology for dental reconstruction to possibly relieving the time-consuming and painful mode-taking process and to open the possibility for computer-assisted inspection and examination. Additionally, a patient's mouth has limited operation space for an injector with a small caliber and a short penetration depth and operation range to cover the entire tooth with a single scan. In other words, reconstruction requires multiple scans for the target region. We relieve its noisy nature with a series of processing stages including optical rectification, frequency-to-depth-density transformation, volumetric boundary detection, and surface reconstruction. Additionally, there are flat regions, such as the mesial side of front teeth, to reduce tracking robustness. We enhance aligning robustness by ensuring a proper initial orientation and enough features in the following two manners. First, we design a scanning order for different types of teeth in order to start from a feature-abundant region; second, we have a 3-axis gyro to track the scanning posture in order to have a better initial orientation for alignment. Furthermore, it is important to immediately examine the alignment results to enhance the scanning success rate. Thus, we accelerate the computation with Graphics Processing Units (GPUs) and streamline the data transfer and computations to have an interactive OCT-based dental scanning framework. Finally, we tested our dental scanner on three isolated teeth and a side of one living tooth with comparable precision against the state-of-art method [4] . Additionally, our system can also reconstruct those parts under gums which the state-of-art fails to achieve. Furthermore, we conduct a usability test to illustrate the importance of visual examination in accelerating the scanning process. Accordingly, we make the following contributions: Optical coherence tomography (OCT) can provide interference responses at the target depth based on its emission frequency for volumetric reconstruction, and thus, we apply this characteristic to develop a tooth gum-penetrative scanner. We overcome the limitations of its noisy imaging, small acquisition caliber, short penetration depth, and short operation range using optical rectification, frequency-to-depth-density transformation, volumetric boundary detection, ordering gyro-assisted point cloud alignment, and Poisson surface reconstruction. Furthermore, it is important to have interactive feedback for examination and to increase the success rate, and thus, we accelerate the rectification, transformation, border detection, and alignment with GPUS and streamline the transfer and processing. As demonstrated in the results, our OCT-based reconstruction framework can properly and efficiently reconstruct teeth while providing intermediate feedback to prevent misses and failure. In other words, this work designs an interactive, harmless, and gum-penetrative OCT-based tooth scanner to precisely reconstruct surfaces for possible mode taking and periodic inspection.
Although Lai et al. REF applied OCT to reconstruct the dental surface, they did not aim at periodontal inspection.
Interactive OCT-Based Tooth Scan and Reconstruction
Sensors (Basel, Switzerland)
Sensors (Basel, Switzerland)
Engineering Computer Science Medicine