![]() In order for volumetric reconstruction, computed tomography (CT) uses X rays to penetrate human tissues and to measure the absorption ratio, and magnetic resonance imaging (MRI) uses various magnetic resonances to locate various tissues. ![]() Furthermore, teeth having complex scattering properties make reconstruction more difficult. However, gums occlude part of teeth to limit their reconstruction ability. Additionally, there are also light detection and ranging (LIDAR)systems, which actively emit laser rays and reconstruct objects by stereoscopic matching or reflected time measurement. Optical reconstruction uses cameras to capture visible light reflected from objects for reconstruction. ![]() There are various digital reconstruction methods. Therefore, this work aims at developing a digital dental reconstruction framework based on harmless, gum-penetrative optical coherent tomography (OCT). Efficient and frequent digital reconstruction may also initiate the possibility of periodic inspection based on newly available artificial intelligence technologies. As a result, it is desired to digitally reconstruct the target part for precision, comfortability, reproductivity, and computer-aided examination. If it is not satisfying, the process repeats. Furthermore, dentists must visually inspect the extraction to determine whether it captures the desired characteristics. Because this process is long and highly uncomfortable, unconscious movements may happen to cause failures. Currently, dentists would have soft impression material on a slot, would hardly press the slot on the target region, and would later remove it from the target to get the mode while the material gets hard enough. Moreover, a user study also verifies the effectiveness of our interactive feedback for efficient and fast clinic scanning.īecause of oral hygiene awareness and advance in dental technologies, modern people generally have dental implants for those root-canal-treated and lost teeth. ![]() 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. 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. 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. However, flat regions, such as the mesial side of front teeth, may not have enough features for alignment. 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. 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. However, optical methods cannot reconstruct those portions under gums, and X-ray-based methods have high radiation to limit their applied frequency. Digital dental reconstruction can be a more efficient and effective mechanism for artificial crown construction and period inspection.
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