Modules:EMSegment-TemplateBuilder-3.4

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Module Name

EM Segment Template Builder

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General Information

Module Type & Category

Type: Interactive

Category: Segmentation

Authors, Collaborators & Contact

  • Kilian Pohl: Harvard/BWH
  • Brad Davis: Kitware, Inc.
  • Sebastien Barre: Kitware, Inc.
  • Yumin Yuan: Kitware, Inc.
  • Polina Golland: MIT
  • Contact: Brad Davis, brad.davis@kitware.com

Module Description

The EMSegment template builder module is the primary Slicer3 interface to the EMSegment algorithm (Pohl et al.), an automatic segmentation algorithm for medical images that previously existed in Slicer 2. The target audience for this module is someone familiar with brain atlases and tissue labels, not a computer scientist. It allows the user to configure the algorithm---step-by-step---to a variety of imaging protocols and anatomical structures, and then apply the algorithm to segment data. Configuration settings are stored in an EMSegment parameters node in the Slicer3 MRML tree. These settings can be saved and later applied to new data via any of the EMSegment interfaces within Slicer3 or the command-line EMSegment executable.

Usage

The purpose of the module is to configure the algorithm to automatically segment anatomical structures in medical images. First the user has to specify parameters defining the image protocol and the anatomical structures of interests. This process results in a template that the module uses to automatically segment large data sets. The template is composed of atlas data and a non-trivial collection of parameters for the EMSegment algorithm.

Once the parameters are specified, the target images are segmented using the EM Segmentation algorithm (Pohl et al.). If the results are satisfactory, the template is saved and can be used later to segment new images (via the GUI or batch processing). If the results are unsatisfactory, the parameters can be modified and the segmentation re-run.

One important aspect of the project is the workflow wizard. This wizard simplifies the module by dividing the complicated template specification task into a number of smaller, intuitive steps.

Examples, Use Cases & Tutorials

  • Note use cases for which this module is especially appropriate, and/or link to examples.
  • Link to examples of the module's use
  • Link to any existing tutorials

Quick Tour of Features and Use

Steps in the Workflow Wizard

  • 1/9 Define Parameters Set: Select parameter set or create new parameters
  • 2/9 Define Hierarchy: Define a hierarchy of anatomical structures
  • 3/9 Assign Atlas: Assign atlases for anatomical structures
  • 4/9 Select Target Images: Choose the set of images that will be segmented
  • 5/9 Intensity Normalization: Normalize target images
  • 6/9 Specify Intensity Distributions: Define intensity distribution for each anatomical structure
  • 7/9 Edit Node-based Parameters: Specify node-based segmentation parameters
  • 8/9 Edit Registration Parameters: Specify atlas-to-target registration parameters
  • 9/9 Run Segmentation: Save work and apply EM Algorithm to segment target images

Development

The overall design of the EMSegmenter module is described in these slides.

The module is implemented as a programmatic Slicer3 module because it requires a large degree of interaction with the user, the data stored in the MRML tree, and the Slicer3 GUI itself. Because the MRML node structure is rather complicated (for example the anatomical tissue hierarchy and a large number of interdependent nodes) the Logic class is solely responsible for maintaining and accessing these nodes. The Logic class provides an API that the GUI code uses to access and modify data. The Logic class also wraps the algorithm code itself.

Dependencies

Slicer3 base modules.

Known bugs

Follow this link to the Slicer3 bug tracker.


Usability issues

The EMSegmenter can be adapted to many segmentation problems. However, there is no "default" set of parameters that will work for all segmentation problems.

  • Atlas-to-target registration and intensity normalization are very important; it will be most effective to apply these steps using algorithms that are customized to your data. Defaults are provided but they may perform poorly for your data---this will lead to poor segmentation results.

Follow this link to the Slicer3 bug tracker. Please select the usability issue category when browsing or contributing.

  • 2008: Working on a single channel T1 version of the parameter set. See here for the Data and such (20meg).


Source code & documentation

Links for the module.


More Information

For more information about the EM Segmenter project in Slicer3 see the old EMSegment Wiki page here

Acknowledgment

Funding for the EMSegmenter module was provided by NAMIC.

References

Pohl K, Bouix S, Nakamura M, Rohlfing T, McCarley R, Kikinis R, Grimson W, Shenton M, Wells W. A Hierarchical Algorithm for MR Brain Image Parcellation. IEEE Transactions on Medical Imaging. 2007 Sept;26(9):1201-1212. [bib]