A Segmentation Enhancement Method for the Low-Contrast and Narrow-Banded Substances in CBCT Images

Due to its low contrast, narrow banded, and emerged to the output imaging attribute scale, facial skin tissue is difficult to extract from dental cone-beam computed tomography (CBCT) reconstructions. Furthermore, there is a challenge of balancing the indication and patient-specific factors and imaging dosage to make it both safe and diagnostically effective for successful treatment planning. These issues make a new frontier for facial skin and soft tissue diagnostic applications driven by sparse dental and low-dose CBCT data. In this study, a new segmentation enhancement method for low-contrast and narrow-banded substances is proposed based on our previous work on selective anatomy analysis iterative reconstruction (SA2IR). The purpose of the proposed method is to segment facial skin tissue based on combinatorial optimization and previously known facial soft tissue structure anatomy. Our results using this method indicated that the skin thickness was much more easily and more quickly identified than with conventional ultrasonic scanning methods. This method holds the potential to be an assisting tool for studying linage of anthropometrics, forensics, human archaeology, and some narrow medico-dental applications.