亚像素渲染
计算机科学
图像配准
计算机视觉
仿射变换
人工智能
光学相干层析成像
刚性变换
模板匹配
光学
数学
像素
图像(数学)
物理
纯数学
作者
David Wei Wei,Anthony J. Deegan,Ruikang K. Wang
标识
DOI:10.1117/1.jbo.22.6.066013
摘要
When using optical coherence tomography angiography (OCTA), the development of artifacts due to involuntary movements can severely compromise the visualization and subsequent quantitation of tissue microvasculatures. To correct such an occurrence, we propose a motion compensation method to eliminate artifacts from human skin OCTA by means of step-by-step rigid affine registration, rigid subpixel registration, and nonrigid B-spline registration. To accommodate this remedial process, OCTA is conducted using two matching all-depth volume scans. Affine transformation is first performed on the large vessels of the deep reticular dermis, and then the resulting affine parameters are applied to all-depth vasculatures with a further subpixel registration to refine the alignment between superficial smaller vessels. Finally, the coregistration of both volumes is carried out to result in the final artifact-free composite image via an algorithm based upon cubic B-spline free-form deformation. We demonstrate that the proposed method can provide a considerable improvement to the final en face OCTA images with substantial artifact removal. In addition, the correlation coefficients and peak signal-to-noise ratios of the corrected images are evaluated and compared with those of the original images, further validating the effectiveness of the proposed method. We expect that the proposed method can be useful in improving qualitative and quantitative assessment of the OCTA images of scanned tissue beds.
科研通智能强力驱动
Strongly Powered by AbleSci AI