Difference between revisions of "2016 Summer Project Week/Uncertainty-aware Information Fusion"

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* The conditioning requires the inversion of an n X n matrix (n is the number of observations).
 
* The conditioning requires the inversion of an n X n matrix (n is the number of observations).
 
* Time complexity O(n^3)
 
* Time complexity O(n^3)
* Identify appropriate formalisms and, if needed, approximation approaches to make calculations fast enough for interventional use.
 
 
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<h3>Approach, Plan</h3>
 
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* Identify appropriate formalisms and, if needed, approximation approaches to make calculations fast enough for interventional use.
 
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Revision as of 11:03, 20 June 2016

Home < 2016 Summer Project Week < Uncertainty-aware Information Fusion

Key Investigators

  • Bojan Kocev, University of Bremen
  • Sarah Frisken, BWH/HMS
  • William Wells, BWH/HMS


Project Description

Uncertainty-aware Information Fusion for Real-time Soft Tissue Motion Estimation. This is part of Boyan's PhD thesis.

Objective

  • Need to fuse motion prior and observations/measurements in an uncertainty-aware fashion.
  • Stochastic processes are a very nice formal mathematical framework which allows for that.
  • Estimating the motion signal value at a given location in the domain requires conditioning the motion prior on the observations.
  • The conditioning requires the inversion of an n X n matrix (n is the number of observations).
  • Time complexity O(n^3)

Approach, Plan

  • Identify appropriate formalisms and, if needed, approximation approaches to make calculations fast enough for interventional use.

Progress