计算机视觉
人工智能
锥束ct
计算机科学
纹理映射
投影纹理映射
稳健性(进化)
医学影像学
图像配准
图像纹理
计算机断层摄影术
医学
图像分割
分割
放射科
图像(数学)
生物化学
化学
基因
作者
Qinyong Lin,Xiongbo Guo,Wenlong Zhang,Lijing Cai,Rongqian Yang,Huazhou Chen,Ken Cai
出处
期刊:IEEE Journal of Biomedical and Health Informatics
[Institute of Electrical and Electronics Engineers]
日期:2023-01-01
卷期号:: 1-10
被引量:27
标识
DOI:10.1109/jbhi.2023.3298708
摘要
The demand for cone-beam computed tomography (CBCT) imaging in clinics, particularly in dentistry, is rapidly increasing. Preoperative surgical planning is crucial to achieving desired treatment outcomes for imaging-guided surgical navigation. However, the lack of surface texture hinders effective communication between clinicians and patients, and the accuracy of superimposing a textured surface onto CBCT volume is limited by dissimilarity and registration based on facial features. To address these issues, this study presents a CBCT imaging system integrated with a monocular camera for reconstructing the texture surface by mapping it onto a 3D surface model created from CBCT images. The proposed method utilizes a geometric calibration tool for accurate mapping of the camera-visible surface with the mosaic texture. Additionally, a novel approach using 3D-2D feature mapping and surface parameterization technology is proposed for texture surface reconstruction. Experimental results, obtained from both real and simulation data, validate the effectiveness of the proposed approach with an error reduction to 0.32 mm and automated generation of integrated images. These findings demonstrate the robustness and high accuracy of our approach, improving the performance of texture mapping in CBCT imaging.
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