Joint analysis of multiple biomarker images and tissue morphology is
important for disease diagnosis, treatment planning and drug development. It
requires cross-staining comparison among Whole Slide Images (WSIs) of
immuno-histochemical and hematoxylin and eosin (H&E) microscopic slides.
However, automatic, and fast cross-staining alignment of enormous gigapixel
WSIs at single-cell precision is challenging. In addition to morphological
deformations introduced during slide preparation, there are large variations in
cell appearance and tissue morphology across different staining. In this paper,
we propose a two-step automatic feature-based cross-staining WSI alignment to
assist localization of even tiny metastatic foci in the assessment of lymph
node. Image pairs were aligned allowing for translation, rotation, and scaling.
The registration was performed automatically by first detecting landmarks in
both images, using the scale-invariant image transform (SIFT), followed by the
fast sample consensus (FSC) protocol for finding point correspondences and
finally aligned the images. The Registration results were evaluated using both
visual and quantitative criteria using the Jaccard index. The average Jaccard
similarity index of the results produced by the proposed system is 0.942 when
compared with the manual registration.
Abubakr Shafique, Morteza Babaie, Mahjabin Sajadi, Adrian Batten, Soma Skdar, H. R. Tizhoosh