Enhancement of Cilia Sub-structures by Multiple Instance Registration and Super-Resolution Reconstruction

摘要

Ultrastructural analysis of cilia cross-sectional images using transmission electron microscopy (TEM) assists the pathologists to diagnose Primary Ciliary Dyskinesia, a genetic disease. The current diagnostic procedure is manual and difficult because of poor signal-to-noise ratio in TEM images. In this paper, we propose an automated multi-step registration approach to register many cilia cross-sectional instances. The novelty of the work is in the utilization of customized weight masks at each registration step to achieve good alignment of the specific cil-ium regions. Registration is followed by super-resolution reconstruction to enhance the substructural information. Landmarks matching based evaluation of registration results in pixel alignment error of 2.35 ± 1.82 pixels, and the subjective analysis of super-resolution reconstructed cil-ium shows a clear improvement in the visibility of the substructures such as dynein arms, radial spokes, and central pair.