2017 Winter Project Week/Population Based Image Imputation - Revision history

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<gallery>
Image:PW-Winter2017.png|link=2017_Winter_Project_Week#Projects|[[2017_Winter_Project_Week#Projects|Projects List]]

Image:PW-Imputation2017.png
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==Key Investigators==
*Adrian Dalca, MIT
*Katie Bouman, MIT
*Polina Golland, MIT

==Project Description==

We developed a model for image imputation - or restoration - for clinical quality images where slice separation (e.g. 6mm) is significantly larger than slice resolution (e.g. 1mm^2). Our model captures statistical correlations within a collection of clinical images from a population of subjects at each location in the image. This means we learn different model parameters for many image locations involving methematical updates that involve many small matrix multiplications. In this project we want to investigate the potential for GPUs to help in the runtime of the algorithm.

{| class="wikitable"
! style="text-align: left; width:27%" | Objective
! style="text-align: left; width:27%" | Approach and Plan
! style="text-align: left; width:27%" | Progress and Next Steps
|- style="vertical-align:top;"
|

* To test (and implement) a GPU version of Population Based Image Imputation, which learns a sparse-observation low-dimensional Gaussian Mixture Model at many locations in an image.
|

* Test whether the type of operations we do (most many many small matrix multiplications and look-up) can be made significantly more efficient on a GPU
* Implement algorithm updates on GPU
* investigate banding side-effects.|

*
|}

==Background and References==

@@ Line 9: / Line 9: @@
 *Adrian Dalca, MIT, MGH
 *Katie Bouman, MIT
-*Mert Sabuncu, MGH
+*Mert Sabuncu, MGH, Cornell
 *Polina Golland, MIT

@@ Line 31: / Line 31: @@
+|
 <!-- Progress and Next steps bullet points (fill out at the end of project week) -->
+* Implemented entire algorithm on GPU.
 |}
 ==Background and References==
 <!-- Use this space for information that may help people better understand your project, like links to papers, source code, or data -->

@@ Line 27: / Line 27: @@
 * Test whether the type of operations we do (most many many small matrix multiplications and look-up) can be made significantly more efficient on a GPU
 * Implement algorithm updates on GPU
-* investigate banding side-effects.|
+* investigate banding side-effects.
 <!-- Progress and Next steps bullet points (fill out at the end of project week) -->
+*