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Título
Patch-based nonlinear image registration for gigapixel whole slide images
Autor
Año del Documento
2016
Editorial
Institute of Electrical and Electronics Engineers
Descripción
Producción Científica
Documento Fuente
IEEE Transactions on biomedical engineering, 2016, Vol. 63, n. 9, p.1812-1819
Résumé
Image registration of whole slide histology images allows the fusion of fine-grained information-like different immunohistochemical stains-from neighboring tissue slides. Traditionally, pathologists fuse this information by looking subsequently at one slide at a time. If the slides are digitized and accurately aligned at cell level, automatic analysis can be used to ease the pathologist's work. However, the size of those images exceeds the memory capacity of regular computers. Methods: We address the challenge to combine a global motion model that takes the physical cutting process of the tissue into account with image data that is not simultaneously globally available. Typical approaches either reduce the amount of data to be processed or partition the data into smaller chunks to be processed separately. Our novel method first registers the complete images on a low resolution with a nonlinear deformation model and later refines this result on patches by using a second nonlinear registration on each patch. Finally, the deformations computed on all patches are combined by interpolation to form one globally smooth nonlinear deformation. The NGF distance measure is used to handle multistain images. Results: The method is applied to ten whole slide image pairs of human lung cancer data. The alignment of 85 corresponding structures is measured by comparing manual segmentations from neighboring slides. Their offset improves significantly, by at least 15%, compared to the low-resolution nonlinear registration. Conclusion/Significance: The proposed method significantly improves the accuracy of multistain registration which allows us to compare different antibodies at cell level.
Materias Unesco
3207.13 Oncología
Palabras Clave
Cancer
Patología digital
Histopatología
Registro de imágenes
ISSN
0018-9294
Revisión por pares
SI
Version del Editor
Propietario de los Derechos
© IEEE
Idioma
eng
Tipo de versión
info:eu-repo/semantics/publishedVersion
Derechos
openAccess
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