Optical coherence tomography (OCT) is a non-invasive imaging method that provide high-resolution tomographic images. Attempts to incorporate OCT in dental practice have been ongoing, but the relatively bulky systems have limited their clinical utility. In this study, we utilized a microelectromechanical system (MEMS) to optimize the size of these OCT scanners to be similar to commercial intra-oral scanner (IOS) products. The optical axis of the internal scanner is designed in a Z shape to maximize the beam size reflected by the MEMS mirrors. To prove its usefulness in practical dentistry, we imaged the teeth in the oral cavity by position. Imaged teeth by position in the oral cavity demonstrated that the developed system can image deep into the oral cavity without difficulty. As a next step, we imaged teeth with cervical abrasion in three dimensions (3D) and high resolution. We classified the teeth into two types based on how the cervix was worn, and the degree of wear was quantitatively analyzed by performing A-scan profiling. This study demonstrates that the developed dental OCT system is effective in actual dental clinical practice and can be utilized for a variety of dental conditions.
KEYWORDS: Cornea, Transplantation, Deep learning, Optical coherence tomography, 3D modeling, Ultrasonography, Time metrology, Medical devices, Image segmentation, Eye
For several decades after corneal transplantation was performed for the first time, studies to predict the success of corneal transplantation have been conducted. To obtain a successful corneal transplantation, various factors other than biocompatibility between the donor cornea and the transplant recipient's eye must be satisfied. Therefore, various studies are being conducted to develop an artificial cornea that does not require a donor. One of the important indicators contributing to the success of corneal transplantation is measurement of corneal thickness (CT) after corneal transplantation. In previous studies, to measure the CT and transplanted cornea, partial CT measurement using an algorithm was mainly performed in optical coherence tomography (OCT) images. However, a single algorithm eventually has limitations in determining the suitability of the entire transplanted cornea. In this study, we automatically segmented the region of the artificial cornea implanted in the rabbit cornea through U-Net based models, and based on this, we measured and analyzed the three-dimensional total thickness of the conventional cornea and the artificial cornea. Our results suggest that the thickness of the transplanted and existing corneas can be automatically measured over time to provide information as an indicator for determining the success of corneal transplants.
One common limitation of spectral-domain optical coherence tomography (SD-OCT) is the mismatch between line-scan camera pixels and the wavelength of the source spectrum, causing image thickening in deeper regions and compromising imaging quality. Various studies have addressed this issue by attempting to improve the alignment between camera pixels and wavelength, with a focus on mitigating the nonlinearity of wavenumbers in SD-OCT systems. To enhance signal quality in deeper imaging regions, several wavenumber linearization (k-linearization) methods have been explored. In our research, we have introduced a novel k-linearization approach based on the diffraction grating equation. The specifications of the light source in our SD-OCT system were utilized for algorithm simulation. Our method concentrated on the difference in diffraction angles at the diffraction grating within the spectrometer to determine the incident wavenumber per pixel. By applying the acquired k-index to our system, we observed an improvement in intensity roll-off and a reduction in the thickening of images in the high-frequency region of the sample. One notable advantage of our proposed method is its effectiveness in obtaining a suitable k-index for systems with simple specifications. Additionally, it can be easily tailored to meet the specific requirements of different systems. This ensures that our approach is not only innovative but also adaptable to diverse SD-OCT setups.
Residual adhesive on tooth surface after bracket removal has to be identified at an advanced stage to avoid further effects on orthodontic and dental procedures, which has to be identified at an advanced stage. Since conventional visual inspection has a major limitation in identifying residuals, non-invasive identification with multi-dimensional assessments using swept-source optical coherence tomography (SS-OCT) is proposed for the precise identification of residual adhesive on the tooth surface during dental bracket replacements. The feasibility was examined using ex-vivo bovine teeth specimens after the removal of orthodontic implant from the tooth surface. Multi-dimensional assessments, such as residual adhesive boundary, color-scaled enface, adhesive area and thickness information were obtained using OCT to confirm the feasibility of the method. The detection algorithm finds the boundary which is between the dental surface and residual adhesive. The residual adhesive is separated based on the boundary. The area of residual adhesive is measured by an optical microscope and the detection algorithm. The difference between the optical microscope and detection algorithm measured area is lower than 10%. The results revealed that the performed OCT assessments can be beneficial for real-time application during orthodontic procedures as a primary inspection tool. Multi-dimensional assessment method used OCT and confirmed feasibility study shows that OCT can be used the detailed novel diagnosis system and effective tools for dental.
Doppler optical coherence tomography (DOCT) is a non-destructive imaging technique designed to measure the movement of a sample by applying the Doppler effect to optical coherence tomography (OCT) signal data. It was designed to acquire a tomography image of the tympanic membrane (TM) and a calculated Doppler signal in real time with OCT using the CUDA parallel processing algorithm while inducing vibration of the TM with an audio signal. Afterwards, the thickness of the TM inside the ROI was measured using software, and the degree of response was analyzed according to the thickness. To measure the tomographic thickness of the TM responding to sound waves, image processing was used to acquire the upper and lower boundaries of the TM. To reduce the error in thickness measurement according to the angle of the TM, the shortest distance between the upper and lower boundaries at each pixel was used to reduce the error in the thickness measurement. In addition, by mapping the thickness information to a two-dimensional array, the movement of the TM in response to sound waves was finally analyzed through a histogram according to the thickness of the TM. Finally, we were able to obtain the tendency of the response according to the thickness of the TM, and quantitatively analyze the change in the reactivity according to the area of the TM.
Photoacoustic microscopy (PAM) is a non-invasive, label-free functional imaging technique that provides high absorption contrast with high spatial resolution. Spatial sampling density and data size are important determinants of the imaging speed of PAM. Therefore, undersampling methods that reduce the number of scanning points are typically adopted to enhance the imaging speed of PAM by increasing the scanning step size. For the reason that undersampling methods sacrifice spatial sampling density, deep learning-based reconstruction methods have been considered as an alternative; however, these methods have been applied to reconstruct the two-dimensional PAM images, which is related to the spatial sampling density. Therefore, by considering the number of data points, data size, and the characteristics of PAM that provides three-dimensional (3D) volume data, in this study, we newly reported deep learning-based fully reconstructing the undersampled 3D PAM data, which is obtained at the actual experiment (i.e., not manually generated). The results of quantitative analyses demonstrate that the proposed method exhibits robustness and outperforms interpolation-based reconstruction methods at various undersampling ratios, enhancing the PAM system performance with 80-times faster-imaging speed and 800-times lower data size. Moreover, the applicability of this method is experimentally verified by upscaling the sparsely sampled test dataset. The proposed deep learning-based PAM data reconstructing is demonstrated to be the closest model that can be used under experimental conditions, effectively shortening the imaging time with significantly reduced data size for processing.
Surgery of chronic otitis media (COM) is a sensitive procedure, where the success rate crucially depends on the surgeon and the significant depth visibility of the surgical microscope. Additionally, videotapes have been frequently adapted for surgical guidance at operation theaters. While these approaches provide great views and assistance during the surgery, it has proven more challenging to derive morphological and volumetric information on subsurface layers of COM. To address this issue, an intra-surgical spectral-domain optical coherence tomography (OCT) microscope system with an extended working distance of 280 mm was developed, which has augmented reality on the ocular eyepiece of a surgical microscope for more effective visualization of morphological structures during mastoidectomy or tympanoplasty. The cross-sectional OCT images guide surgeons to more easily identify targeted regions by displaying depth direction information in real-time during surgery. Three patients with COM participated in this study, and the lesion conditions of the temporal bone were observed with pre-operative computed tomography (CT) before the surgery. Moreover, pure tone audiogram examinations were performed to evaluate pre- and post-surgical conditions. The pure tone audiogram reveals that the operation was well performed based on the air-bone gap (ABG) reduction, and it can be confirmed that the hearing level was also improved. The success of the surgical procedure was confirmed through the intraoperative OCT images, and the post-examined audiogram results further confirmed the improvement of hearing. Hence, the integration of intra-surgical OCT and audiogram inspection methods revealed the potential merits of the proposed methodology.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.