A robust method for inter-marker whole slide registration of digital pathology images using lines based features

An automated image registration method is proposed for registration of digital whole slide scans of adjacent tissue sections. An example workflow is where a pathologist annotates a tumor region in a primary (H&E1) stained image and the corresponding regions, in nearby sections, stained with other biomarkers, are identified and analyzed for aiding in clinical diagnosis. The different markers convey different clinical information leading to a more comprehensive analysis. This registration process, if done manually, is tedious and time-consuming. We propose a two-pass algorithm. A lines-based approach, computed from tissue boundary regions, returns the global transformation. Then normalized correlation, based on gradient magnitude images, is used for more precise local matching in a multi-resolution approach. The algorithm is robust to flips, large rotation angles, tissue wear-and-tear, and Area of Interest (AOI2) mismatch, and outperforms state-of-the-art registration methods for digital pathology images.