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SUMMARY:Geometrical Growth Models for Computational Anatomy - Irene Kalten
 mark (Aix Marseille Université)
DTSTART:20171114T160000Z
DTEND:20171114T164500Z
UID:TALK95017@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:In the field of computational anatomy\, the Large Deformation 
 Diffeomorphic Metric Mapping (LDDMM) framework has proved to be highly eff
 icient for addressing the problem of modeling and analysis of the variabil
 ity of populations of shapes\, allowing for the direct comparison and quan
 tization of diffeomorphic morphometric changes. However\, the analysis of 
 medical imaging data also requires the processing of more complex changes\
 , which especially appear during growth or aging phenomena. The observed o
 rganisms are subject to transformations over time that are no longer diffe
 omorphic\, at least in a biological sense. One reason might be a gradual c
 reation of new material uncorrelated to the preexisting one. The evolution
  of the shape can then be described by the joint action of a deformation p
 rocess and a creation process.<br>For this purpose\, we offer to extend th
 e LDDMM framework to address the problem of non diffeomorphic structural v
 ariations in longitudinal data. We keep the geometric central concept of a
  group of deformations acting on embedded shapes. The necessity for partia
 l mappings leads to a time-varying dynamic that modifies the action of the
  group of deformations. Ultimately\, growth priors are integrated into a n
 ew optimal control problem for assimilation of time-varying surface data\,
  leading to an interesting problem in the field of the calculus of variati
 ons where the choice of the attachment term on the data\, current or varif
 old\, plays an unexpected role.<br><br>The underlying minimization problem
  requires an adapted framework to consider a new set of cost functions (pe
 nalization term on the deformation). This new model is inspired by the dep
 loyment of animal horns and will be applied to it.&nbsp\;<br><br>Keywords:
  computational anatomy\, growth model\, shape spaces\, Riemannian metrics\
 , group of diffeomorphisms\, large deformations\, variational methods\, op
 timal control.&nbsp\;
LOCATION:Seminar Room 1\, Newton Institute
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