Combined local and global image registration and its application to large-scale images in digital pathology
Johannes Lotz · 2020
A large-scale, nonlinear image registration problem can be partitioned into smaller independent subproblems by adding a global, coarsely discretized distance measure. The remaining inconsistencies between subdomains are smaller than without the coarse distance term and can be incorporated into the global solution by a blending method. Reaching a similar accuracy, the new method enables the registration of large-scale images that could otherwise not be computed. Cite as: Lotz, Johannes. (2020). Combined local and global image registration and its application to large-scale images in digital pathology, University of Lübeck, http://d-nb.info/1217024069, https://doi.org/10.5281/zenodo.4030986 @thesis{lotz_johannes_combined_2020, title = {Combined local and global image registration and its application to large-scale images in digital pathology}, rights = {Creative Commons Attribution 4.0 International, Open Access}, url = {http://d-nb.info/1217024069}, institution = {University of Lübeck}, type = {phdthesis}, author = {Lotz, Johannes}, editora = {Modersitzki, Jan and Handels, Heinz}, editoratype = {collaborator}, urldate = {2020-09-15}, date = {2020-05-05}, langid = {english}, note = {https://doi.org/10.5281/zenodo.4030986}, keywords = {image registration, histopathology, digital pathology, large-scale} }