The traditional navigation interface was intended only for two-dimensional observation by doctors; thus, this interface does not display the total spatial information for the lesion area. Surgical navigation systems have become essential tools that enable for doctors to accurately and safely perform complex operations. The image navigation interface is separated from the operating area, and the doctor needs to switch the field of vision between the screen and the patient’s lesion area. In this paper, augmented reality (AR) technology was applied to spinal surgery to provide more intuitive information to surgeons. The accuracy of virtual and real registration was improved via research on AR technology. During the operation, the doctor could observe the AR image and the true shape of the internal spine through the skin. To improve the accuracy of virtual and real registration, a virtual and real registration technique based on an improved identification method and robot-assisted method was proposed. The experimental method was optimized by using the improved identification method. X-ray images were used to verify the effectiveness of the puncture performed by the robot. The final experimental results show that the average accuracy of the virtual and real registration based on the general identification method was 9.73 ± 0.46 mm (range 8.90–10.23 mm). The average accuracy of the virtual and real registration based on the improved identification method was 3.54 ± 0.13 mm (range 3.36–3.73 mm). Compared with the virtual and real registration based on the general identification method, the accuracy was improved by approximately 65%. The highest accuracy of the virtual and real registration based on the robot-assisted method was 2.39 mm. The accuracy was improved by approximately 28.5% based on the improved identification method. The experimental results show that the two optimized methods are highly very effective. The proposed AR navigation system has high accuracy and stability. This system may have value in future spinal surgeries.

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Optimization of virtual and real registration technology based on augmented reality in a surgical navigation system

Micro-electro-mechanical systems (MEMS) scanner has significant advantages of miniature size, fast response and high stability, which is particularly applicable to photoacoustic laparoscopy (PAL). However, tilt angle-voltage curve of electrothermal MEMS shows a nonlinear character, which leads to inevitable nonlinear distortion in photoacoustic imaging. To overcome this problem, a nonlinear distortion correction was developed for the high-resolution forward-scanning electrothermal-MEMS-based PAL. The adaptive resampling method (ARM) was introduced to adaptively calibrate the projection of non-uniform scanning region to match the uniform scanning region. The correction performed low time complexity and high portability owing to the adaptive capacity of distortion decomposition in the reconstruction of physical models. Compared with the sample structure, phantom experiments demonstrated that the distortion was calibrated in all directions and the corrected image provided up to 96.82% high structural similarity in local subset. Furthermore, ARM was applied to imaging the abdominal cavity of rat and the vascular morphology was corrected in real-time display within a delay less than 2 seconds. All these results demonstrated that the nonlinear distortion correction possessed timely and effective correction in PAL, which suggested that it had the potential to employ to any other electrothermal-MEMS-based photoacoustic imaging systems for accurate and quantitative functional imaging.

Electrothermal-MEMS-induced nonlinear distortion correction in photoacoustic laparoscopy.

The characterization and correction of lens distortion is an important part of optical measurement. This work analyzes the formation mechanism of color fringes and multiplication moire, and discusses modification of the color CCD moire method for correcting lens distortion. A demosaicing algorithm was used to simulate the color fringes in a CCD moire pattern. We then performed a detailed analysis of the carrier field, and adopted a universal polynomial distortion model to characterize lens distortion, which increased the accuracy of distortion correction. Comparison experiments verified the feasibility of the modified method and the correctness of the formation mechanism for color CCD moire. The modified method was then applied to lens distortion correction in the DIC measurement process, effectively reducing errors in displacement measurement.

Modified color CCD moiré method and its application in optical distortion correction

The dimensions of phenotyping parameters such as the thickness of rice play an important role in rice quality assessment and phenotyping research. The objective of this study was to propose an automatic method for extracting rice thickness. This method was based on the principle of binocular stereovision but avoiding the problem that it was difficult to directly match the corresponding points for 3D reconstruction due to the lack of texture of rice. Firstly, the shape features of edge, instead of texture, was used to match the corresponding points of the rice edge. Secondly, the height of the rice edge was obtained by way of space intersection. Finally, the thickness of rice was extracted based on the assumption that the average height of the edges of multiple rice is half of the thickness of rice. According to the results of the experiments on six kinds of rice or grain, errors of thickness extraction were no more than the upper limit of 0.1 mm specified in the national industry standard. The results proved that edge features could be used to extract rice thickness and validated the effectiveness of the thickness extraction algorithm we proposed, which provided technical support for the extraction of phenotyping parameters for crop researchers.

https://www.mdpi.com/1424-8220/19/24/5561/pdf

Novel and Automatic Rice Thickness Extraction Based on Photogrammetry Using Rice Edge Features.

The design concepts of the surface topology control system based on Moire effect are proposed. The system consists of the processor module, the laser emitters’ module, a digital camera, the imaginary raster forming module, the decision-making block. In the developed system the laser emitters’ block is proposed as a projection device, which is possible to increase the accuracy of projecting contrast strips on the object's surface. Due to the case-based concept the system execution algorithm supports intellectual decision making. The decision-making block is able to be integrated with a data pre-processing program. According to this recommendations for processing of precedents using neural networks are given..

Hongye Zhang

Papers

Camera lens distortion evaluation and correction technique based on a colour CCD moiré method