Robust Quad-Tree based Registration on Whole Slide Images
Proceedings of the MICCAI Workshop on Computational Pathology, PMLR 156:181-190, 2021.
The registration of whole slide images (WSIs) provides the basis for many subsequent processing steps in digital pathology. For instance, the registration of immunohistochemistry (IHC) and hematoxylin & eosin (H&E)-stained WSIs is usually the first step in guiding IHC diagnostic procedures. Still, many registration methods operate poorly on WSIs. Reasons for this include the WSI size, fluctuating image quality or elastic tissue deformations. Multiple prior methods are further specialised towards a specific image modality, such as histology or cytology, or rely on a specific preparation protocol. To minimise these effects, we developed a robust WSI registration, which differs from previous methods by the following new aspect: We introduce a multi-scale approach based on a quad-tree (QT), with several termination criteria that makes the algorithm particularly insensitive to tissue artefacts and that further allows to estimate a piece-wise affine transformation. We validated our method on five scanner systems and 60 WSIs with different stainings. Our results outperformed any publicly available WSI registration method. The QT code, WSI landmarks and tools used to create the validation dataset are made publicly available.