Kearney Vasant, Huang Yihui, Mao Weihua, Yuan Baohong, Tang Liping
Department of Radiation Oncology, University of California, San Francisco, CA, USA. Department of Bioengineering, University of Texas Arlington, Arlington, TX, USA.
Phys Med Biol. 2017 Feb 7;62(3):966-985. doi: 10.1088/1361-6560/aa5342. Epub 2017 Jan 12.
This work focuses on developing a 2D Canny edge-based deformable image registration (Canny DIR) algorithm to register in vivo white light images taken at various time points. This method uses a sparse interpolation deformation algorithm to sparsely register regions of the image with strong edge information. A stability criterion is enforced which removes regions of edges that do not deform in a smooth uniform manner. Using a synthetic mouse surface ground truth model, the accuracy of the Canny DIR algorithm was evaluated under axial rotation in the presence of deformation. The accuracy was also tested using fluorescent dye injections, which were then used for gamma analysis to establish a second ground truth. The results indicate that the Canny DIR algorithm performs better than rigid registration, intensity corrected Demons, and distinctive features for all evaluation matrices and ground truth scenarios. In conclusion Canny DIR performs well in the presence of the unique lighting and shading variations associated with white-light-based image registration.
这项工作专注于开发一种基于二维Canny边缘的可变形图像配准（Canny DIR）算法，用于对在不同时间点拍摄的体内白光图像进行配准。该方法使用稀疏插值变形算法对具有强边缘信息的图像区域进行稀疏配准。实施了一个稳定性标准，去除那些不以平滑均匀方式变形的边缘区域。使用合成小鼠表面真实模型，在存在变形的情况下，对Canny DIR算法在轴向旋转下的准确性进行了评估。还使用荧光染料注射进行了准确性测试，然后将其用于伽马分析以建立第二个真实情况。结果表明，对于所有评估矩阵和真实情况场景，Canny DIR算法的性能优于刚性配准、强度校正的Demons算法和特征点方法。总之，在与基于白光的图像配准相关的独特光照和阴影变化情况下，Canny DIR算法表现良好。
