  Motivation: High resolution 2D whole slide imaging provides rich information
about the tissue structure. This information can be a lot richer if these 2D
images can be stacked into a 3D tissue volume. A 3D analysis, however, requires
accurate reconstruction of the tissue volume from the 2D image stack. This task
is not trivial due to the distortions that each individual tissue slice
experiences while cutting and mounting the tissue on the glass slide.
Performing registration for the whole tissue slices may be adversely affected
by the deformed tissue regions. Consequently, regional registration is found to
be more effective. In this paper, we propose an accurate and robust regional
registration algorithm for whole slide images which incrementally focuses
registration on the area around the region of interest. Results: Using mean
similarity index as the metric, the proposed algorithm (mean $\pm$ std: $0.84
\pm 0.11$) followed by a fine registration algorithm ($0.86 \pm 0.08$)
outperformed the state-of-the-art linear whole tissue registration algorithm
($0.74 \pm 0.19$) and the regional version of this algorithm ($0.81 \pm 0.15$).
The proposed algorithm also outperforms the state-of-the-art nonlinear
registration algorithm (original : $0.82 \pm 0.12$, regional : $0.77 \pm 0.22$)
for whole slide images and a recently proposed patch-based registration
algorithm (patch size 256: $0.79 \pm 0.16$ , patch size 512: $0.77 \pm 0.16$)
for medical images. Availability: The C++ implementation code is available
online at the github repository:
https://github.com/MahsaPaknezhad/WSIRegistration
