Modules:FastMarchingSegmentation-Documentation-3.5

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Fast Marching Segmentation

FastMarchingSegmentation

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General Information

Module Type & Category

Type: Interactive

Category: Segmentation

Authors, Collaborators & Contact

• Andriy Fedorov, BWH
• Eric Pichon
• Contact: Andriy Fedorov, fedorov at bwh

Module Description

This module implements segmentation based on fast marching algorithm.

Usage

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

List all the panels in your interface, their features, what they mean, and how to use them. For instance:

• Input panel:
• Parameters panel:
• Output panel:
• Viewing panel:

Development

Features under development:

• add volume rendering -- DONE
• add range control widget to simplify result adjustment -- DONE
• add progress reporting -- DONE
• add ability to initialize with label, not only with fiducials
• documentation
• simplify output label initialization process (selector widget) -- DONE
• integration with Editor
• switch active fiducial list when a new one is added -- DONE
• add parameter node
• Ron: specify the target segmented volume in either mm^3 or cm^3 or major dimensions (1x2x4cm)
• add volume rendering on/off capability -- DONE

Dependencies

Other modules or packages that are required for this module's use.

Known bugs

Follow this link to the Slicer3 bug tracker.

• Execution time of one of the algorithm components is O(max_image_intensity^2). A temporary workaround if the execution time is not acceptabe is to rescale the image to have intensity range of about 600 for reasonable performance. In the future, this step will be done automatically by the implementation.

Usability issues

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

Source code & documentation

Source code can accessed here

Links to documentation generated by doxygen.

More Information

Acknowledgment

Supported by Brain Science Foundation.

References

• Pichon E, Tannenbaum A, Kikinis R. A statistically based flow for image segmentation. Med Image Anal. 2004 Sep;8(3):267-74. PMID: 15450221. [1]