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Home < Documentation < Nightly < Modules < SlicerModuleCardiacRegistrationBRAINSFit

Introduction and Acknowledgements

Authors: Salma Bengali, Alan Morris, CARMA Center, University of Utah
Contributors: Greg Gardner, Josh Cates, Rob MacLeod, CARMA Center, University of Utah
Contacts: Salma Bengali: <email></email>, Alan Morris: <email></email>

Carma UofU logo.jpg

Module Description

This module implements case-specific registration using BRAINSFit for cardiac LGE-MRI, MRA and CT images acquired at different time points or across different patients. The types of registration scenarios are described here. The inputs to this module are two image volumes: image volume one is the fixed volume, and image volume two is the moving volume. The user selects the imaging modalities based on the types of input image volumes. Registration parameters are tuned for the registration cases. Input image volumes that are cropped to the area around the left atrium can also be used to improve the final registration result. Advanced registration parameters can be changed to check if the registration result shows improvement.

Use Cases

(L to R) Registered image, fixed image, and moving image


  • The image volumes in this dataset: CARMA Registration Tutorial Data can be used as inputs to the module. The dataset contains anonymized LGE-MRI, MRA and CT images.

Panels and their use

The following are the inputs and outputs:

  • Image Volume One (Fixed): Select the LGE-MRI, MRA or CT Image
  • Image Volume Two (Moving): Select the LGE-MRI or MRA image
  • Output Image Volume: The registration result
  • Imaging modality: The types of image volumes that are being registered (e.g LGE-MRI, MRA, CT, Acute Scar)

The advanced registration parameters are:

  • Initialization Type
  • Registration Type
  • Maximum Number of Iterations
  • Number of Samples
  • Minimum Step Length
  • Transform Scale
  • Reproportion Scale
  • Skew Scale
  • Interpolation Type
  • Metric Type

The details about the advanced registration parameters can be found at

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Information for Developers

The source code for this module can be found at the CARMA GitHub repository.