Modules:ABC-Documentation-3.5
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Atlas Based Classification
Atlas Based Classification
(Documentation in progress)
General Information
Module Type & Category
Type: CLI
Category: Segmentation
Authors, Collaborators & Contact
- Marcel Prastawa, Utah
- Guido Gerig, Utah
- Contact: Marcel Prastawa, prastawa@sci.utah.edu
Module Description
ABC (Atlas Based Classification) is a full segmentation pipeline developed and used at University of North Carolina and University of Utah for healthy brain MRIs. The processing pipeline includes image registration, filtering, and inhomogeneity correction.
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
Input images. First image in the list is the reference image space. All other images are registered to first image. |
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* Atlas Panel
Atlas information. Atlas directory contains the template file (template.mha), and the prior probabilities (1.mha, ..., 999.mha) Orientation: RAI, ASR, LPS, etc Prior weight adjustments: space separated numbers, must be the same number as number of priors. |
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* Output Panel
Specify where to store output files (optional). Segmentation label image, and bias corrected image. |
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* Advanced Panel
Advanced parameters |
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Development
Dependencies
None
Known bugs
Follow this link to the bug tracker at NITRC.
Source code & documentation
Available at [1]