An ITK Filter for Bayesian Segmentation: itkBayesianClassifierImageFilter
Georgia Institute of Technology; Kitware
| Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/160 |
Published in The Insight Journal - 2006 January - June.
Submitted by John Melonakos on 12-04-2006.
An Insight Toolkit (ITK) filter for image segmentation with
applications to brain MRI scans is presented in this paper. Previously, we
showed how ITK could be used to implement our algorithm. This paper
presents our new ITK filter for Bayesian segmentation along with results
on brain MRI scans. Our algorithm is a refinement of the work of Teo,
Saprio, and Wandall. The basic idea is to incorporate prior knowledge
into the segmentation through Bayes rule. Image noise is removed via an
affine invariant anisotropic smoothing of the posteriors as in Haker et. al.
Specifically, we present the implementation of our Bayesian segmentation
algorithm applied to brain MRI scans.
applications to brain MRI scans is presented in this paper. Previously, we
showed how ITK could be used to implement our algorithm. This paper
presents our new ITK filter for Bayesian segmentation along with results
on brain MRI scans. Our algorithm is a refinement of the work of Teo,
Saprio, and Wandall. The basic idea is to incorporate prior knowledge
into the segmentation through Bayes rule. Image noise is removed via an
affine invariant anisotropic smoothing of the posteriors as in Haker et. al.
Specifically, we present the implementation of our Bayesian segmentation
algorithm applied to brain MRI scans.
Data
13 Files (253Kb)
segmented-png-files.zip (13Kb)
raw-png-files.zip (37Kb)
BayesianClassifier.cxx (5Kb)
BayesianClassifierInitializer.cxx (6Kb)
itkBayesianClassificationImageFilter.txx (3Kb)
itkBayesianClassificationImageFilter.h (4Kb)
itkBayesianClassifierImageFilter.txx (12Kb)
itkBayesianClassifierInitializationImageFilter.txx (11Kb)
itkBayesianClassifierInitializationImageFilter.h (7Kb)
itkBayesianClassificationImageFilterTest.cxx (1Kb)
melonakos-IJ2006-bayesian.pdf (138Kb) [view paper]
itkBayesianClassifierImageFilter.h (9Kb)
CMakeLists.txt (1Kb)
raw-png-files.zip (37Kb)
BayesianClassifier.cxx (5Kb)
BayesianClassifierInitializer.cxx (6Kb)
itkBayesianClassificationImageFilter.txx (3Kb)
itkBayesianClassificationImageFilter.h (4Kb)
itkBayesianClassifierImageFilter.txx (12Kb)
itkBayesianClassifierInitializationImageFilter.txx (11Kb)
itkBayesianClassifierInitializationImageFilter.h (7Kb)
itkBayesianClassificationImageFilterTest.cxx (1Kb)
melonakos-IJ2006-bayesian.pdf (138Kb) [view paper]
itkBayesianClassifierImageFilter.h (9Kb)
CMakeLists.txt (1Kb)
Code
Automatic Testing Results
by Insight-Journal Dashboard
on Fri Feb 3 13:18:19 2006 for revision #3 
expertise: 5 sensitivity: 4.5 
This project was submitted with no test cases.Click here for more details.
Go here to access the main testing dashboard.
Automatic Testing Results
by Insight-Journal Dashboard
on Thu Jan 26 16:47:56 2006 for revision #2 expertise: 5 sensitivity: 5
Automatic Testing Results
by Insight-Journal Dashboard
on Fri Jan 20 10:37:25 2006 for revision #1 expertise: 5 sensitivity: 5 Reviews
Bayesian segmentation algorithm
by Vamsi Jammalamadaka on 02-13-2006 for revision #3 expertise: 2 sensitivity: 4.5
Summary:
This filter implements Bayesian Segmentation technique.
Open Science:
This is clearly Open Source code.
Reproducibility:
I was able to download, compile, and run the work.
I tested it on 3d MR images and the results look great!
Use of Open Source Software:
It is written completely in itk
Code Quality:
The code is easy to read and very well documented.
Additional Comments:
A very well presented paper with clear explanation of the algorithm.
It is a very useful application for segmenting MRI images.
This filter implements Bayesian Segmentation technique.
Open Science:
This is clearly Open Source code.
Reproducibility:
I was able to download, compile, and run the work.
I tested it on 3d MR images and the results look great!
Use of Open Source Software:
It is written completely in itk
Code Quality:
The code is easy to read and very well documented.
Additional Comments:
A very well presented paper with clear explanation of the algorithm.
It is a very useful application for segmenting MRI images.
Statistics
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| Global rating: | 
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| Review rating: | [review]
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| Code rating: |  
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| Views: | 4169 |
| Downloads: | 743 |
Send a message to the author
Information
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| Paper Id: | 69 |
| Keywords: | Segmentation, Bayesian, ITK, Brains, |
| Toolkit: | ITK (moved into the toolkit) |
| Revision: | 3 (02-03-2006) |
| Status: | Open for public review |
Data
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| Full download: | .zip |
| Paper: | view, .pdf |
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