ArticleJournal of pathology informatics2021
Improving Algorithm for the Alignment of Consecutive, Whole-Slide, Immunohistochemical Section Images.
Article in Journal of pathology informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- [Virtual histopathology of the pancreas: 3D insights using synchrotron-based imaging].Pathologie (Heidelberg, Germany) · 2026Article
- From traditional to deep learning approaches in whole slide image registration: A methodological review.Journal of pathology informatics · 2025Review
- Alignment of histological and polarimetric large-scale imaging for brain tissue characterization.Journal of biomedical optics · 2025Article
- Blueprints from plane to space: outlook of next-generation three-dimensional histopathology.Cancer science · 2024Review
- CD3-CD8 immune score associated with a clinical score stratifies PDAC prognosis regardless of adjuvant or neoadjuvant chemotherapy.Oncoimmunology · 2024Article
- Virtual alignment of pathology image series for multi-gigapixel whole slide images.Nature communications · 2023Article
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAccurate and precise alignment of histopathology tissue sections is a key step for the interpretation of the proteome topology and cell level three-dimensional (3D) reconstruction of diseased tissues. However, the realization of an automated and robust method for aligning nonglobally stained immunohistochemical (IHC) sections is still challenging. In this study, we aim to assess the feasibility of multidimensional graph-based image registration on aligning serial-section and whole-slide IHC section images. MATERIALS AND
methodsAn automated, patch graph-based registration method was established and applied to align serial, whole-slide IHC sections at ×10 magnification (average 32,947 × 27,054 pixels). The alignment began with the initial alignment of high-resolution reference and translated images (object segmentation and rigid registration) and nonlinear registration of low-resolution reference and translated images, followed by the multidimensional graph-based image registration of the segmented patches, and finally, the fusion of deformed patches for inspection. The performance of the proposed method was formulated and evaluated by the Hausdorff distance between continuous image slices.
resultsSets of average 315 patches from five serial whole slide, IHC section images were tested using 21 different IHC antibodies across five different tissue types (skin, breast, stomach, prostate, and soft tissue). The proposed method was successfully automated to align most of the images. The average Hausdorff distance was 48.93 μm with a standard deviation of 14.94 μm, showing a significant improvement from the previously published patch-based nonlinear image registration method (average Hausdorff distance of 93.89 μm with 50.85 μm standard deviation).
conclusionsOur method was effective in aligning whole-slide tissue sections at the cell-level resolution. Further advancements in the screening of the proteome topology and 3D tissue reconstruction could be expected.
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