2016 JRNL PP J. Lotz - 1.pdf
Terbatas  Irwan Sofiyan
» Gedung UPT Perpustakaan
Terbatas  Irwan Sofiyan
» Gedung UPT Perpustakaan
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.