Multi-staining registration of large histology images

Quantifying T cells inside tumorous tissue can help identifying immune profiles in order to improve prognosis and possibly develop immunotherapy. However, to identify T cells and cancerous cells in two consecutive staining slides is challenging: the tissue preparation introduces the problem of align...

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Bibliographic Details
Published in2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) pp. 345 - 348
Main Authors Gonzalez Obando, Daniel F., Frafjord, Astri, Oynebraten, Inger, Corthay, Alexandre, Olivo-Marin, Jean-Christophe, Meas-Yedid, Vannary
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2017
Subjects
Computational modeling
Deformable models
deformable registration
Histology registration
image analysis
Image registration
Image resolution
Immune system
Prognostics and health management
Splines (mathematics)
whole slide imaging
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Summary:Quantifying T cells inside tumorous tissue can help identifying immune profiles in order to improve prognosis and possibly develop immunotherapy. However, to identify T cells and cancerous cells in two consecutive staining slides is challenging: the tissue preparation introduces the problem of alignment on large size images with poor visual common information. This work presents a framework for aligning whole slide images by extracting their common information and performing non-rigid registration based on B-splines to solve this problem. Experiments show good results with a mean error of 20.34 ± 12.20μm on our images even if some developments are still needed. This preliminary work is publicly available as part of our open-source Icy platform.
ISSN:1945-8452
DOI:10.1109/ISBI.2017.7950534