Abstract
Probabilistic atlas has broad applications in medical image segmentation and registration. The most common problem building a probabilistic atlas is picking a target image upon which to map the rest of the training images. Here we present a method to choose a target image that is the closest to the mean geometry of the population under consideration as determined by bending energy. Our approach is based on forming a distance matrix based on bending energies of all pair-wise registrations and performing multidimensional scaling (MDS) on the distance matrix.
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Park, H., Bland, P.H., Hero, A.O., Meyer, C.R. (2005). Least Biased Target Selection in Probabilistic Atlas Construction. In: Duncan, J.S., Gerig, G. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005. MICCAI 2005. Lecture Notes in Computer Science, vol 3750. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11566489_52
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DOI: https://doi.org/10.1007/11566489_52
Publisher Name: Springer, Berlin, Heidelberg
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