光学相干层析成像眼底视网膜三维图像去抖动方法
|
摘要
眼底视网膜病变是大部分眼科疾病的来源。光学相干层析成像(OCT)具有无创性、成像安全快速等特点,在临床上被广泛用于眼科疾病的诊断。针对OCT视网膜三维图像因抖动产生的扭曲变形问题,提出一种基于曲线拟合的OCT视网膜三维重建图像去抖动方法,即通过预处理提取OCT视网膜图像的边界,再利用最小二乘法曲线拟合来计算各帧切片图像的偏移量。结果表明:所提方法对OCT视网膜三维重建图像扭曲变形具有明显的校正作用。
Fundus retinopathy is the cause of most ophthalmic diseases. Optical coherence tomography(OCT) has been widely used in the diagnosis of ophthalmic diseases because of its non-invasive and rapid imaging features. In this paper, a dither removing method is proposed for three-dimensional OCT retinal image based on curve fitting. The OCT retina image boundary is extracted by preprocessing, and the offset of each frame slice image is calculated by least squares curve fitting. The results show that the proposed method has a significant correction effect on the distortion of the OCT retina three-dimensional reconstructed images.
Fundus retinopathy is the cause of most ophthalmic diseases. Optical coherence tomography(OCT) has been widely used in the diagnosis of ophthalmic diseases because of its non-invasive and rapid imaging features. In this paper, a dither removing method is proposed for three-dimensional OCT retinal image based on curve fitting. The OCT retina image boundary is extracted by preprocessing, and the offset of each frame slice image is calculated by least squares curve fitting. The results show that the proposed method has a significant correction effect on the distortion of the OCT retina three-dimensional reconstructed images.
引文
[1] Jack J K. Differential diagnosis map of eye and systemic diseases[M]. Fuzhou: Fujian Science & Technology Publishing House, 2002. 肯思基. 眼与全身疾病鉴别诊断图谱[M]. 福州: 福建科技出版社, 2002.
[2] Wilkins G R, Houghton O M, Oldenburg A L. Automated segmentation of intraretinal cystoid fluid in optical coherence tomography[J]. IEEE Transactions on Biomedical Engineering, 2012, 59(4): 1109-1114.
[3] Tang Z S. 3D data field visualization[M]. Beijing: Tsinghua University Press, 2009: 10-30.
[4] Lowe D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 2004, 60(2): 91-110.
[5] Yang S, Yang C L. Image registration algorithm based on sparse random projection and scale-invariant feature transform[J]. Acta Optica Sinica, 2014, 34(11): 1110001. 杨飒, 杨春玲. 基于压缩感知与尺度不变特征变换的图像配准算法[J]. 光学学报, 2014, 34(11): 1110001.
[6] Manduchi R, Mian G A. Accuracy analysis for correlation-based image registration algorithms[C]//The IEEE International Symposium on Circuits and Systems, 1993: 834- 837.
[7] Maes F, Collignon A, Vandermeulen D, et al. Multimodality image registration by maximization of mutual information[J]. IEEE Transactions on Medical Imaging, 1997, 16(2): 187-198.
[8] Perona P, Malik J. Scale-space and edge detection using anisotropic diffusion[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(7): 629-639.
[9] Canny J. A computational approach to edge detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, PAMI-8(6): 679-698.
[10] Chen G, Ren Z L, Sun H Z. Curve fitting in least-square method and its realization with Matlab[J]. Ordnance Industry Automation, 2005, 24(3): 107-108. 陈光, 任志良, 孙海柱. 最小二乘曲线拟合及Matlab实现[J]. 兵工自动化, 2005, 24(3): 107- 108.
[2] Wilkins G R, Houghton O M, Oldenburg A L. Automated segmentation of intraretinal cystoid fluid in optical coherence tomography[J]. IEEE Transactions on Biomedical Engineering, 2012, 59(4): 1109-1114.
[3] Tang Z S. 3D data field visualization[M]. Beijing: Tsinghua University Press, 2009: 10-30.
[4] Lowe D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 2004, 60(2): 91-110.
[5] Yang S, Yang C L. Image registration algorithm based on sparse random projection and scale-invariant feature transform[J]. Acta Optica Sinica, 2014, 34(11): 1110001. 杨飒, 杨春玲. 基于压缩感知与尺度不变特征变换的图像配准算法[J]. 光学学报, 2014, 34(11): 1110001.
[6] Manduchi R, Mian G A. Accuracy analysis for correlation-based image registration algorithms[C]//The IEEE International Symposium on Circuits and Systems, 1993: 834- 837.
[7] Maes F, Collignon A, Vandermeulen D, et al. Multimodality image registration by maximization of mutual information[J]. IEEE Transactions on Medical Imaging, 1997, 16(2): 187-198.
[8] Perona P, Malik J. Scale-space and edge detection using anisotropic diffusion[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(7): 629-639.
[9] Canny J. A computational approach to edge detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, PAMI-8(6): 679-698.
[10] Chen G, Ren Z L, Sun H Z. Curve fitting in least-square method and its realization with Matlab[J]. Ordnance Industry Automation, 2005, 24(3): 107-108. 陈光, 任志良, 孙海柱. 最小二乘曲线拟合及Matlab实现[J]. 兵工自动化, 2005, 24(3): 107- 108.