Project Week 25/Slice-to-Volume Registration to Support MRI guided Interventions

From NAMIC Wiki
Revision as of 11:00, 30 June 2017 by GGulamhussene (talk | contribs)
Jump to: navigation, search
Home < Project Week 25 < Slice-to-Volume Registration to Support MRI guided Interventions


Back to Projects List

Key Investigators

Project Description

Objective Approach and Plan Progress and Next Steps
  • The objective of this project is to drive the discussion under which circumstances medical image registration can be used to support MRI guided liver interventions.
  • Furthermore a simple implementation of a state of the art method to register iMRI to MRI shall show the principle possibility of such an approach.
  • discuss the applicability of Slice-to-Volume registration of intra-interventional MRI to pre-interventional MRI to support liver interventions. (insights from radiologists would be valuable)
  • give an overview of factors that determin the applicability of (StV) registration to support liver interventions in MRI
  • implement state of the art algorithm to register orthogonal iMRI slices to MRI volume

Progress

  • discussed the motivation for non-regit registration of planing MRI/CT to iMRI/iCT
    • reducing the need of contrast agend administration in both iMRI and iCT
    • providing any additional information that is either containt in planning data or added / annotated in its reference frame
    • providing additional information from other modalities like PET (Pre-fusing several planing volumes)
    • reducing mental effort for interventionalist
  • I got showed a manual workflow in Slicer to solve the basic task with state of the art methods
  • I got insights into the development with and for Slicer
  • I started to implement a python Slicer Extension to automate the previously found workflow using several aspects of slicer (CLI, Python Scripting, simpleITK, sitkUtils)

Next Steps

  • finishing the Slicer extension
  • implementing a way to generate ground truth (simulated respiration deformation in iMRI)
  • implementing the evaluation tools (visual inspection and computed metrics)

Illustrations

Background and References