Difference between revisions of "2016 Winter Project Week/Projects/PatchRegistration"

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Here, we are investigating a patch-based discrete image registration which allows for more versatile image metrics and does not impose similar assumptions.
 
Here, we are investigating a patch-based discrete image registration which allows for more versatile image metrics and does not impose similar assumptions.
  
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* We will investigate a current implementation for patch-based discrete registration on sparse-slice data.
 
* We will investigate a current implementation for patch-based discrete registration on sparse-slice data.
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Revision as of 22:20, 18 December 2015

Home < 2016 Winter Project Week < Projects < PatchRegistration

Key Investigators

  • Adrian Dalca (MIT)
  • Andreea Bobu (MIT)
  • Polina Golland (MIT)

Project Description

Due to the low quality of clinical images (often with many artifacts, 7mm thick slices, etc), most standard algorithms, such as those for registration, segmentation, and analysis, will fail. In part, this is because registration algorithm depend on assumptions of smooth anatomical structures and good quality images, which are not present in these sparse clinical acquisitions. Here, we are investigating a patch-based discrete image registration which allows for more versatile image metrics and does not impose similar assumptions.

Objective
  • We will investigate a current implementation for patch-based discrete registration on sparse-slice data.
 Approach, Plan
Progress
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