Diffeomorphic brain shape modelling using Gauss-Newton optimisation

19 Jun 2018Yaël BalbastreMikael BrudforsKevin BronikJohn Ashburner

Shape modelling describes methods aimed at capturing the natural variability of shapes and commonly relies on probabilistic interpretations of dimensionality reduction techniques such as principal component analysis. Due to their computational complexity when dealing with dense deformation models such as diffeomorphisms, previous attempts have focused on explicitly reducing their dimension, diminishing de facto their flexibility and ability to model complex shapes such as brains... (read more)

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