To meet the needs of real-time imaging in intraoperative microsurgical vessel anastomosis and to break through the bottleneck of limited penetration depth caused by absorption and scattering from blood, we present a novel design of three-view cooperative scanning handheld OCT probe. It is based on a low coherence source with 1.3μm central wavelength for extra-vascular imaging. Traditional OCT probe always scan from one direction and suffers from the problem of incomplete cross-sectional view of the vessel under investigation. We've designed an MEMS mirror based OCT handheld probe, which can be used to generate cross-sectional images from 3 view directions to increase the field of view in the depth direction. In addition, to adapt to vessels of different sizes, we've also designed a micro-stage to be used together with the handheld probe to solve the hand-trembling problem. The rectangle scanning range is about 3 * 3mm in three-view, which can meet the imaging demands of most vessels. We believe that application of the probe will greatly improve the quality of micro-vascular anastomosis success rate.
To solve the 2π phase ambiguity for phase-resolved Doppler images in Doppler optical coherence tomography, we present a modified network programming technique for the first time to the best of our knowledge. The proposed method assumes that error of the discrete derivatives between unwrapped phase image and wrapped phase image can be arbitrary values instead of integer-multiple of 2π, which makes the real-phase restoration accurate and robust against noise. We compared our proposed method with the network programming method. Parameters including root-mean-square-error and noise amplification degree were adopted for comparison. The experimental study on simulated images, phantom, and real-vessel OCT images were performed. The proposed method consistently achieves optimal results.
Partial differential equation (PDE)-based nonlinear diffusion processes have been widely used for image denoising. In the traditional nonlinear anisotropic diffusion denoising techniques, behavior of the diffusion depends highly on the gradient of image. However, it is difficult to get a good effect if we use these methods to reduce noise in optical coherence tomography images. Because background has the gradient that is very similar to regions of interest, so background noise will be mistaken for edge information and cannot be reduced. Therefore, nonlinear complex diffusion approaches using texture feature(NCDTF) for noise reduction in phase-resolved optical coherence tomography is proposed here, which uses texture feature in OCT images and structural OCT images to remove noise in phase-resolved OCT. Taking into account the fact that texture between background and signal region is different, which can be linked with diffusion coefficient of nonlinear complex diffusion model, we use NCDTF method to reduce noises of structure and phase images first. Then, we utilize OCT structure images to filter phase image in OCT. Finally, to validate our method, parameters such as image SNR, contrast-to-noise ratio (CNR), equivalent number of looks (ENL), and edge preservation were compared between our approach and median filter, Gaussian filter, wavelet filter, nonlinear complex diffusion filter (NCDF). Preliminary results demonstrate that NCDTF method is more effective than others in keeping edges and denoising for phase-resolved OCT.
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