Li Mu, Lu Yanmeng, Han Shuaihu, Wu Zhuobin, Chen Jiajing, Liu Zhexing, Cao Lei
School of Biomedical Engineering, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.E-mail:
Nan Fang Yi Ke Da Xue Xue Bao. 2015 Aug;35(9):1251-7.
We proposed a new stitching method based on sift features to obtain an enlarged view of transmission electron microscopic (TEM) images with a high resolution. The sift features were extracted from the images, which were then combined with fitted polynomial correction field to correct the images, followed by image alignment based on the sift features. The image seams at the junction were finally removed by Poisson image editing to achieve seamless stitching, which was validated on 60 local glomerular TEM images with an image alignment error of 62.5 to 187.5 nm. Compared with 3 other stitching methods, the proposed method could effectively reduce image deformation and avoid artifacts to facilitate renal biopsy pathological diagnosis.
我们提出了一种基于尺度不变特征变换（SIFT）特征的新拼接方法，以获得具有高分辨率的透射电子显微镜（TEM）图像的放大视图。从图像中提取SIFT特征，然后将其与拟合的多项式校正场相结合以校正图像，接着基于SIFT特征进行图像对齐。最后通过泊松图像编辑去除交界处的图像接缝以实现无缝拼接，该方法在60张局部肾小球TEM图像上得到验证，图像对齐误差为62.5至187.5纳米。与其他3种拼接方法相比，该方法可有效减少图像变形并避免伪影，便于肾活检病理诊断。
