2016 Winter Project Week/Projects/PatchRegistration

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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 Approach and Plan Progress and Next Steps
  • We will investigate a current implementation for patch-based discrete registration on sparse-slice data.
  • We have an implementation of patch-based discrete registration using a standard patch distance metric. We'll start by evaluating this current metric on isotropic images
  • We'll develop a new metric for sparse images and test it out.