Multiple transmission electron microscopic image stitching based on sift features.
- Author:
Mu LI
1
;
Yanmeng LU
;
Shuaihu HAN
;
Zhuobin WU
;
Jiajing CHEN
;
Zhexing LIU
;
Lei CAO
Author Information
1. School of Biomedical Engineering, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.E-mail: hello_limu@163.com.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Artifacts;
Humans;
Image Processing, Computer-Assisted;
methods;
Kidney Glomerulus;
ultrastructure;
Microscopy, Electron, Transmission;
methods
- From:
Journal of Southern Medical University
2015;35(9):1251-1257
- CountryChina
- Language:Chinese
-
Abstract:
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.
