期刊
SENSORS
卷 21, 期 6, 页码 -出版社
MDPI
DOI: 10.3390/s21062200
关键词
lateral cephalogram; Gaussian mixture model; image registration; image fusion
资金
- national natural science foundation of China [61801069]
- natural science foundation of Chongqing, China [cstc2020jcyj-msxmX0702, CSTC2017ZDCYzdyfX0049]
A panoramic image stitching algorithm for dental multifunctional Cone Beam Computed Tomography is proposed in this study, achieving image registration and fusion through various techniques, showing promising results in experimental evaluations.
In the design of dental multifunctional Cone Beam Computed Tomography, the linear scanning strategy not only saves equipment cost, but also avoids the demand for patients to be repositioned when acquiring lateral cranial sequence images. In order to obtain panoramic images, we propose a local normalized cross-correlation stitching algorithm based on Gaussian Mixture Model. Firstly, the Block-Matching and 3D filtering algorithm is used to remove quantum and impulse noises according to the characteristics of X-ray images; Then, the segmentation of the irrelevant region and the extraction of the region of interest are performed by Gaussian Mixture Model; The locally normalized cross-relation is used to complete the registration with the multi-resolution strategy based on wavelet transform and Particle Swarm Optimization algorithm; Finally, image fusion is achieved by the weighted smoothing fusion algorithm. The experimental results show that the panoramic image obtained by this method has significant performance in both subjective vision and objective quality evaluation and can be applied to preoperative diagnosis of clinical dental deformity and postoperative effect evaluation.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据