Morphable Models for the Analysis and Synthesis of Complex Motion Patterns
International Journal of Computer Vision - special issue on learning and vision at the center for biological and computational learning, Massachusetts Institute of Technology
Spatio-Temporal Alignment of Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Increasing Space-Time Resolution in Video
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Confidence measure for temporal registration of recurrent non-uniform samples
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
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Four-dimensional (4D) visualization of medical data, which entails the addition of time as the fourth dimension to 3D data, is fast gaining ground as a tool for diagnosis and surgical planning by medical practitioners. However, current medical image acquisition techniques do not support high-resolution 4D capture. Instead, multiple 3D datasets are acquired and a temporal relation is computed between these datasets in order to align them in time. In past work we presented a method of temporal alignment of MRI datasets to generate high-resolution medical data, which can be extended to 4D visualization. In this work, we present the details of our temporal alignment algorithm and also present comparative analysis in order to highlight the advantages of our method.