2014 Summer Project Week:Stroke-SuperResolution

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  Projects List

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  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.

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