Difference between revisions of "2016 Summer Project Week/Uncertainty-aware Information Fusion"
From NAMIC Wiki
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<h3>Objective</h3> | <h3>Objective</h3> | ||
* Need to fuse motion prior and observations/measurements in an uncertainty-aware fashion. | * 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) | ||
* Identify appropriate formalisms and, if needed, approximation approaches to make calculations fast enough for interventional use. | * Identify appropriate formalisms and, if needed, approximation approaches to make calculations fast enough for interventional use. | ||
</div> | </div> | ||
Revision as of 11:01, 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)
- Identify appropriate formalisms and, if needed, approximation approaches to make calculations fast enough for interventional use.
