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An End-to-end Pipeline for 3D Slide-wise Multi-stain Renal Pathology Registration

arXiv 2305.11968 ↗First posted 19 May 2023eess.IV cs.CVcited by 0

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Abstract (arXiv)

Tissue examination and quantification in a 3D context on serial section whole slide images (WSIs) were laborintensive 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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 3 of its 9 references that are in the map. First posted on arXiv 19 May 2023.

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3 of 9 references.

References · 3

  1. 2019SuperGlue: Learning Feature Matching with Graph Neural Networkscited by 1,437
  2. 2020CircleNet: Anchor-free Detection with Circle Representationcited by 19
  3. 2020Map3D: Registration Based Multi-Object Tracking on 3D Serial Whole Slide Imagescited by 5

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