View source for 2016 Summer Project Week/Uncertainty-aware Information Fusion

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Image:PW-Summer2016.png|[[2016_Summer_Project_Week#Projects|Projects List]]
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==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.

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<h3>Objective</h3>
* 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)
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<h3>Approach, Plan</h3>
* Identify appropriate formalisms and, if needed, approximation approaches to make calculations fast enough for interventional use.
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<h3>Progress</h3>
* 
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