Publication | Closed Access
Multi-staining registration of large histology images
19
Citations
8
References
2017
Year
Unknown Venue
EngineeringWhole-slide ImagingLarge Histology ImagesDigital PathologyImmunologyHistologyPathologyT CellsImmunotherapyWhole Slide ImagesImage AnalysisImage RegistrationComputational ImagingImmune ProfilesMedical ImagingHistopathologyComputational PathologyBiomedical AnalysisImage StitchingMedical Image ComputingCell BiologyTumor MicroenvironmentMicroscope Image ProcessingBioimage AnalysisBiomedical ImagingMedicineCell Detection
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.
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