Difference between revisions of "2014 Summer Project Week:Stroke-SuperResolution"

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Image:PW-MIT2014.png|[[2014_Summer_Project_Week#Projects|Projects List]]
 
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Image:WMH_T1.png|Clinical Stroke Image
 
Image:STROKE_SR1.png|Super-Resolution initial results -- top-left is a 'real' image, from which we simulate a 1x1x7mm clinical image. The bottom images are state of the art interpolations. The top right is our current result.
 
Image:STROKE_SR1.png|Super-Resolution initial results -- top-left is a 'real' image, from which we simulate a 1x1x7mm clinical image. The bottom images are state of the art interpolations. The top right is our current result.
 
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Revision as of 16:02, 23 June 2014

Home < 2014 Summer Project Week:Stroke-SuperResolution

Key Investigators

- Adrian Dalca, Ramesh Sridharan, Polina Golland, MIT

Project Description

To improve results for Large Datasets of clinical-quality data, we are investigating super-resolution methods. Here, we are using a patch-based approach with MRF priors and utilizing only the current dataset, without an external training dataset.


Objective

  • We will investigate/implement a scale-space MRF inference based on patch search results.

Approach, Plan

  • We are developing a patch library in MATLAB, and need to apply it in a scale-space framework to the T2-FLAIR dataset.

Progress