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Tissue examination and quantification in a 3D context on serial section whole slide images (WSIs) were labor-intensive
and time-consuming tasks. Our previous study proposed a novel registration-based method (Map3D)
to automatically align WSIs to the same physical space, reducing the human efforts of screening serial sections
from WSIs. However, the registration performance of our Map3D method was only evaluated on single-stain
WSIs with large-scale kidney tissue samples. In this paper, we provide a Docker for an end-to-end 3D slide-wise
registration pipeline on needle biopsy serial sections in a multi-stain paradigm. The contribution of this study is
three-fold: (1) We release a containerized Docker for an end-to-end multi-stain WSI registration. (2) We prove
that the Map3D pipeline is capable of sectional registration from multi-stain WSI. (3) We verify that the Map3D
pipeline can also be applied to needle biopsy tissue samples. The source code and the Docker have been made
publicly available at https://github.com/hrlblab/Map3D.
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Peize Li, Ruining Deng, Yuankai Huo, "An end-to-end pipeline for 3D slide-wise multi-stain renal pathology registration," Proc. SPIE 12471, Medical Imaging 2023: Digital and Computational Pathology, 124710F (6 April 2023); https://doi.org/10.1117/12.2654542