TY - JOUR
T1 - Temporal ordering and registration of images in studies of developmental dynamics
AU - Dsilva, Carmeline J.
AU - Lim, Bomyi
AU - Lu, Hang
AU - Singer, Amit
AU - Kevrekidis, Ioannis G.
AU - Shvartsman, Stanislav Y.
N1 - Publisher Copyright:
© 2015. Published by The Company of Biologists Ltd.
PY - 2015
Y1 - 2015
N2 - Progress of development is commonly reconstructed from imaging snapshots of chemical or mechanical processes in fixed tissues. As a first step in these reconstructions, snapshots must be spatially registered and ordered in time. Currently, image registration and ordering are often done manually, requiring a significant amount of expertise with a specific system. However, as the sizes of imaging data sets grow, these tasks become increasingly difficult, especially when the images are noisy and the developmental changes being examined are subtle. To address these challenges, we present an automated approach to simultaneously register and temporally order imaging data sets. The approach is based on vector diffusion maps, a manifold learning technique that does not require a priori knowledge of image features or a parametric model of the developmental dynamics. We illustrate this approach by registering and ordering data from imaging studies of pattern formation and morphogenesis in three model systems. We also provide software to aid in the application of our methodology to other experimental data sets.
AB - Progress of development is commonly reconstructed from imaging snapshots of chemical or mechanical processes in fixed tissues. As a first step in these reconstructions, snapshots must be spatially registered and ordered in time. Currently, image registration and ordering are often done manually, requiring a significant amount of expertise with a specific system. However, as the sizes of imaging data sets grow, these tasks become increasingly difficult, especially when the images are noisy and the developmental changes being examined are subtle. To address these challenges, we present an automated approach to simultaneously register and temporally order imaging data sets. The approach is based on vector diffusion maps, a manifold learning technique that does not require a priori knowledge of image features or a parametric model of the developmental dynamics. We illustrate this approach by registering and ordering data from imaging studies of pattern formation and morphogenesis in three model systems. We also provide software to aid in the application of our methodology to other experimental data sets.
KW - Drosophila
KW - Image registration
KW - Temporal ordering
KW - Vector diffusion maps
KW - Zebrafish
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U2 - 10.1242/dev.119396
DO - 10.1242/dev.119396
M3 - Article
C2 - 25834019
AN - SCOPUS:84928645757
SN - 0950-1991
VL - 142
SP - 1717
EP - 1724
JO - Journal of Embryology and Experimental Morphology
JF - Journal of Embryology and Experimental Morphology
IS - 9
ER -