Projects:RegistrationDocumentation:ParameterTesting

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ISMRM abstract 2010

• Title: MR-protocol Tailored Medical Image Registration
• Objective: Determine optimized sets of parameters for successful automated registration of MR-MR images within the 3DSlicer software. DOF, cost function, initialization and optimization strategy will differ because of the differences in image contrast and/or content. This work will present approaches and solutions for successful registration for a large set of combinations of MRI pairings. This is part of a concerted effort to build a Registration Case Library available to the medical imaging research community.
• Method:
  • 1- we choose 3-4 subjects/exams with 3-4 different contrast pairings: T1, T2, PD, FLAIR: ~12-16 images
  • 2- we have an expert reader determine ~ 3-5 anatomical landmarks on each unregistered image
  • 3- we register all combinations and run a sensitivity analysis for the most critical parameters: 6 vs. 12 DOF, cost function, % sampling
  • 4- outcome metric is RMS error of fiducial alignment
  • 5- we report the best performing parameter set for each MR-MR combination
  • 6-extension 1: add different voxel sizes, i.e. emulate 1,3,5mm slice thickness
  • 7- extension 2: add initial misalignment as parameter to the test series
• Options: The expert landmark selection as rate-limiting step we could bypass by doing this as a self-validation where we start from a registration we consider optimal and then apply pre-determined misalignment. We then do not need fiducial pairs to evaluate but can derive RMS metrics from the result Xform directly. We will have to justify/scrutinize how we chose our gold-standard. A true gold-standard would exist only for prospectively aligned image sets, such as a dual echo PD/T2.
• sensitivity analysis we report as line plots comparing RMS ranges for different metrics, e.g. compare MI vs. NCorr