title: [Multiple transmission electron microscopic image stitching based on sift features].
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.
authors.affiliation: School of Biomedical Engineering, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.E-mail: hello_limu@163.com.
authors.forename: Mu
authors.initials: M
authors.lastname: Li
authors.forename: Yanmeng
authors.initials: Y
authors.lastname: Lu
authors.forename: Shuaihu
authors.initials: S
authors.lastname: Han
authors.forename: Zhuobin
authors.initials: Z
authors.lastname: Wu
authors.forename: Jiajing
authors.initials: J
authors.lastname: Chen
authors.forename: Zhexing
authors.initials: Z
authors.lastname: Liu
authors.forename: Lei
authors.initials: L
authors.lastname: Cao
mesh_terms: D000465:Algorithms; D016477:Artifacts; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007678:Kidney Glomerulus / Q000648:ultrastructure; D046529:Microscopy, Electron, Transmission / Q000379:methods*