基于局部血管结构特征的眼底图像二级配准

提出了一种结合全局配准和局部配准技术的眼底图像二级配准算法, 该算法采用4个相连的分叉点组成的局部血管结构来代替单独的分叉点作为配准特征, 通过减少配对点集, 提高了配准效率.同时针对非线性形变造成的局部配准偏移较大的问题, 在全局配准基础上进一步采用局部配准技术, 提升了配准的准确度.实验结果表明, 该算法以很高的配准效率和准确度有效实现了眼底图像的配准.

Abstract

A two-stage registration algorithm combining global registration and local registration technology is proposed. In this algorithm, bifurcation structures with 4 connected bifurcation points rather than single bifurcation points are used as the registration features. By reducing pairing points, the efficient of registration is improved. Moreover due to non-linear deformation, there are some registration errors appear in some local region. To solve this problem, a local registration technology is introduced according to the global registration results, which improve registration precision. Experiment results show that the algorithm effectively achieve fundus image registration with higher efficient and precision.

参考文献

[1] MATSOPOULOS G K, ASVESTAS P A, MOURAVLI- ANSKY N A, et al. Multimodal registration of retinal images using self organizing maps［J］. IEEE Transactions on Medical Imaging, 2004, 23(12): 1557-1563.

[2] FERNANDES M, GAVET Y, PINOLI J C. A feature-based dense local registration of pairs of retinal Images［C］. VISAPP: Proceedings of the 4th International Conference on Computer VISion Theory and APplications, 2009.

[3] TAHA H M, BENDARY N E, HASSANIEN A E, et al. Retinal feature-based registration scheme［J］.Communications in Computer and Information Science, 2011, 252(1): 26-36.

[4] 游嘉.眼底图像融合的研究及系统实现［D］. 重庆:重庆大学,2011.

[5] RITTER N, OWENS R, COOPER J, et al. Registration of stereo and temporal images of the retina［J］. IEEE Transactions on Medical Imaging, 1999, 18(5): 404-418.

[6] CHOE T E, COHEN I, LEE M, et al. Optimal global mosaic generation from retinal images［C］. 18th International Conference on Pattern Recognition, 2006, 3: 681-684.

[7] CAN A, STEWART C, ROYSAM B, et al. A feature-based, robust, hierarchical algorithm for registering pairs of images of the curved human retina［J］.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(3): 347-364.

[8] STEWART C V, TSAI C L, ROYSAM B. The dual-bootstrap iterative closest point algorithm with application to retinal image registration［J］. IEEE Transactions on Medical Imaging, 2003, 22(11): 1379-1394.

[9] LALIBERTE F, GAGNON L, SHENG Yun-long. Registration and fusion of retinal images-An evaluation study［J］. IEEE Transactions on Medical Imaging, 2003, 22(5): 661-673.

[10] 张波. 基于ICP和SVD的眼底图像配准研究［D］.长春:吉林大学,2009.

[11] CHEN L, ZHANG X L. Feature-based image registration using bifurcation structures［C］. Brussels, 2011: 2169-2172.

[12] 王鑫. 图像配准理论及其算法研究［D］.哈尔滨:哈尔滨工程大学,2005.

[13] 韩松涛. 眼底图像的血管特征分析［D］. 长春:吉林大学,2010.

沈奔, 张东波, 彭英辉. 基于局部血管结构特征的眼底图像二级配准[J]. 光子学报, 2012, 41(10): 1236. SHEN Ben, ZHANG Dong-bo, PENG Ying-hui. Two-stage Retinal Fundus Image Registration Based on Local Blood Structure Features[J]. ACTA PHOTONICA SINICA, 2012, 41(10): 1236.

基于局部血管结构特征的眼底图像二级配准

关于本站 Cookie 的使用提示

全站搜索

基于局部血管结构特征的眼底图像二级配准

相关论文

相关资讯

关于本站 Cookie 的使用提示

全站搜索