Symmetric Log-Domain Diffeomorphic Registration: A Demons-Based Approach
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Contributions to 3D diffeomorphic atlas estimation: application to brain images
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Which reorientation framework for the atlas-based comparison of motion from cardiac image sequences?
STIA'12 Proceedings of the Second international conference on Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data
Geodesic shape regression in the framework of currents
IPMI'13 Proceedings of the 23rd international conference on Information Processing in Medical Imaging
Geodesics, Parallel Transport & One-Parameter Subgroups for Diffeomorphic Image Registration
International Journal of Computer Vision
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Follow-up imaging studies require the evaluation of the anatomical changes over time for specific clinical groups. The longitudinal changes for a specific subject can be evaluated through the non-rigid registration of successive anatomical images. However, to perform a longitudinal group-wise analysis, the subject-specific longitudinal trajectories of anatomical points need to be transported in a common reference frame. In this work, we propose the Schild's Ladder framework as an effective method to transport longitudinal deformations in time series of images in a common space using diffeomorphic registration. We illustrate the computational advantages and demonstrate the numerical accuracy of this very simple method by comparing with standard methods of transport on simulated images with progressing brain atrophy. Finally, its application to the clinical problem of the measurement of the longitudinal progression in the Alzheimer's disease suggests that an important gain in sensitivity could be expected on group-wise comparisons.