An ITK Filter for Bayesian Segmentation: itkBayesianClassifierImageFilter
Melonakos J., Krishnan K., Tannenbaum A.
Georgia Institute of Technology; Kitware

Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/160
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.
Data
minus 13 Files (253Kb)
Code
minus Automatic Testing Results by Insight-Journal Dashboard on Fri Feb 3 13:18:19 2006 for revision #3
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plus Automatic Testing Results by Insight-Journal Dashboard on Thu Jan 26 16:47:56 2006 for revision #2
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plus Automatic Testing Results by Insight-Journal Dashboard on Fri Jan 20 10:37:25 2006 for revision #1
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Reviews
minus Bayesian segmentation algorithm by Vamsi Jammalamadaka on 02-13-2006 for revision #3
starstarstarstarstar expertise: 2 sensitivity: 4.5
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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.
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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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Associated Publications
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User-Guided Level Set Segmentation of Anatomical Structures with ITK-SNAP
Segmentation of Skull-infiltrated Tumors Using ITK: Methods and Validation
A Framework for Algorithm Evaluation and Clinical Application Prototyping using ITK

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