Probabilistic image registration and anomaly detection by nonlinear warping
Automatic, defect tolerant registration of transmission electron microscopy (TEM) images poses an important and challenging problem for biomedical image analysis, e.g. in computational neuroanatomy. In this paper we demonstrate a fully automatic stitching and distortion correction method for TEM images and propose a probabilistic approach for image registration that implicitly detects image defects due to sample preparation and image acquisition. The approach uses a polynomial kernel expansion to estimate a non-linear image transformation based on intensities and spatial features. Corresponding...