Slicer3:EM

Project Summary

The goal of this project is the creation of a module in Slicer 3 integrating the EMSegment algorithm (Pohl et al.), an automatic segmentation algorithm for medical images that previously existed in Slicer 2. As in Slicer 2, the user is able to adjust the algorithm to a variety of imaging protocols as well as anatomical structures and run the segmenter on large data set. However, the configuration of the algorithm is greatly simplified in Slicer 3 as the user is guided by a work flow. The target audience for this module is someone familiar with brain atlases and tissue labels, not a computer scientist.

As of January 1, 2007, the EMSegment module is substantially complete and has been checked into the Slicer3 SVN repository. It was previewed at the December 2006 NAMIC meeting in Clifton Park and will be a demonstration at the NAMIC All-Hands meeting in Salt Lake City on Wednesday 10 January 2007. Future work includes adding advanced and experimental algorithm parameters, improving visualization of parameter settings, and incorporating tissue labels from a controlled vocabulary.

Contacts

• MIT/BWH: Kilian Pohl (pohl@csail.mit.edu)
• Kitware: Brad Davis (brad.davis@kitware.com)

Project Description

As stated above, the goal of this project is to provide the functionality of the EMSegment algorithm as a Slicer3 module. A similar EMSegment module is available in Slicer2.6. The intent of this project is to implement a Slicer3 module with similar functionality while also improving the graphical user interface (GUI). While the GUI and data structure (MRML) code was completely rewritten for the Slicer3 module, the algorithm code was not modified.

High-level Module Description

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.

Steps in EMSegment Workflow

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

Status

A version of the Slicer3 EMSegment module has been completed and checked into the Slicer3 SVN repository. Example data have been packaged and will soon be available from this wiki page. A tutorial is under development and will be presented at the January 2007 NAMIC All-Hands Meeting by K. Pohl and B. Davis.

While there is a completed working version of the module it will likely be under development for some time. The primary future development efforts will be for (1) bug fixing, (2) adding new functionality, (3) modifying the underlying code to make better use of the evolving Slicer3 base functionality.

Completed

• finalize workflow description (Kilian, Wendy, Brad)
• define new MRML node structure (Kilian, Brad)
• implement workflow wizard (Sebastien, Luis)
• document workflow wizard and write tutorial (Sebastien)
• implement core MRML classes/attributes (Brad)
• implement logic class that manages MRML nodes and provides API to GUI (Brad)
• implement user interface for each wizard step (Yumin, Sebastien)
• create example data and parameter set (Kilian, Brad)
• port algorithm code from Slicer2 (Brad)
• create tutorial (Kilian, Brad)

In Progress

• bug fixes
• intensity distribution widget
• incorporate feedback from core Slicer developers into design

Future Work

• run algorithm in a different thread (with progress bars)
• incorporate rules for when user may go to next step in workflow
• add registration to module
• simplified interface---only load template, load images on (panel 1), start segmentation (like EMAtlasBrainClassifier)
• add standardized tissue labels; need to elaborate on specification
• intensity distribution widget
• incorporate PCA parameters into GUI
• incorporate Class Interaction Matrix parameters into GUI
• add class overview widget
• add step for prior intensity normalization across scanners
• undo/redo
• testing
• expand updating based on MRML events

Implementation Details

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.

EMSegment Tutorial

To try out the module with the tutorial data:

1. build the latest version of Slicer3
2. download and untar the data file below (it is approximately 43 megabytes zipped and 329 megabytes unzipped)
3. start Slicer3
4. choose File->Import Scene... and select the file EMSegmentTutorial/Data/EMSegmentTutorialTemplate.mrml from the location where you untared the data
   1. a number of images and MRML nodes will be loaded, this may take some time depending on the speed of you computer and file access
5. in Slicer3 change to the EMSegment module
6. in step 1 of the module make sure that parameter node 100 is selected (that is the one that was loaded in the previous step)
7. use the "Next" and "Back" buttons to navigate through the module, viewing and updating parameters as you go
   1. Note: no parameters need to be modified to run the segmentation using the default tutorial settings
8. on step 8/8, select "Run" and the segmentation will start
   1. the segmentation takes approximately 2.5 minutes on a dual core Intel processor with 2 gigabytes of memory
   2. by default the resulting segmentation is saved in the Segmentation_Result image

Tutorial: Slides Data

Screen Shot