Difference between revisions of "2016 Summer Project Week/Uncertainty-aware Information Fusion"
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Revision as of 13:08, 24 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 Bojan'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
- Identified a number of possible approaches that could be used for speeding up the inversion of the n x n matrix. Implemented and tested one of these approaches.
