Difference between revisions of "Collaboration/Iowa/Meshing/Migrate Iowa Neural Net code to pure ITK"

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|[[Image:ProjectWeek-2007.png|thumb|320px|Return to [[2007_Programming/Project_Week_MIT|Project Week Main Page]] ]]
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|[[Image:Hand-Atlas.jpg|thumb|left|250px|Atlas Hand Image]]
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|[[Image:Hand-Subject.jpg|thumb|left|250px|Subject Hand Image]]
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|[[Image:Hand-WarpedAtlas.jpg|thumb|left|250px|Warped Atlas Image]]
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<h1>Approach, Plan</h1>
 
<h1>Approach, Plan</h1>
  
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Our approach for analyzing diffusion tensors is summarized in the IPMI 2007 reference below. The main challenge to this approach is <foo>.
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Integrate additional ITK transform types into the neural network using the general ITK transform I/O mechanism. Evaluate the changes to segment the phalanx bones bones of the hand.
  
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Our plan for the project week is to first try out <bar>,...
 
 
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<h1>Progress</h1>
 
<h1>Progress</h1>
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Two milestones were reached in this effort.
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*The first was that we have integrated a rigid body initialization for a Thirion Demons registration for atlas <-> subject registration. The above modification was used to warp the atlas to the subject as shown in the figures.
  
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Software for the fiber tracking and statistical analysis along the tracts has been implemented. The statistical methods for diffusion tensors are implemented as ITK code as part of the [[NA-MIC/Projects/Diffusion_Image_Analysis/DTI_Software_and_Algorithm_Infrastructure|DTI Software Infrastructure]] project. The methods have been validated on a repeated scan of a healthy individual. This work has been published as a conference paper (MICCAI 2005) and a journal version (MEDIA 2006). Our recent IPMI 2007 paper includes a nonparametric regression method for analyzing data along a fiber tract.
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*The second was that the neural network code now supports all ITK transforms for registration of the atlas<->subject. This was achieved using the itkTransformReader and the a templated function over the image type and transform type to resample the images.
  
 
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===References===
 
===References===
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* Fletcher, P.T., Tao, R., Jeong, W.-K., Whitaker, R.T., "A Volumetric Approach to Quantifying Region-to-Region White Matter Connectivity in Diffusion Tensor MRI," to appear Information Processing in Medical Imaging (IPMI) 2007.
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* Magnotta VA, Heckel D, Andreasen NC, Cizadlo T, Corson PW, Ehrhardt JC, Yuh WT. "Measurement of brain structures with artificial neural networks: two- and three-dimensional applications", Radiology 211 (1999), 781-90.
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* Corouge, I., Fletcher, P.T., Joshi, S., Gilmore, J.H., and Gerig, G., "Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis," Medical Image Analysis 10 (2006), 786--798.
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* Powell S, Magnotta VA, Johnson HJ, Jammalamadaka VK, Andreasen NC. "Registration and Machine Learning Based Automated Segmentation of Subcortical and Cerebellar Brain Structures", NeuroImage, In Press.
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* Corouge, I., Fletcher, P.T., Joshi, S., Gilmore J.H., and Gerig, G., Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis, Lecture Notes in Computer Science LNCS, James S. Duncan and Guido Gerig, editors, Springer Verlag, Vol. 3749, Oct. 2005, pp. 131 -- 138
 
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* C. Goodlett, I. Corouge, M. Jomier, and G. Gerig, A Quantitative DTI Fiber Tract Analysis Suite, The Insight Journal, vol. ISC/NAMIC/ MICCAI Workshop on Open-Source Software, 2005, Online publication: http://hdl.handle.net/1926/39 .
 

Latest revision as of 02:59, 29 June 2007

Home < Collaboration < Iowa < Meshing < Migrate Iowa Neural Net code to pure ITK
Return to Project Week Main Page
Atlas Hand Image
Subject Hand Image
Warped Atlas Image




Key Investigators

  • Iowa: Vincent Magnotta and Nicole Grosland
  • Kitware: Stephen Alyward

Objective

Conversion of the Iowa Neural netwok segmentation using a flexible module for image registration supporting all ITK transforms written using the transform I/O in ITK. Conversion to the ITK neural network from the current annie implementation may also be

Approach, Plan

Integrate additional ITK transform types into the neural network using the general ITK transform I/O mechanism. Evaluate the changes to segment the phalanx bones bones of the hand.

Progress

Two milestones were reached in this effort.

  • The first was that we have integrated a rigid body initialization for a Thirion Demons registration for atlas <-> subject registration. The above modification was used to warp the atlas to the subject as shown in the figures.
  • The second was that the neural network code now supports all ITK transforms for registration of the atlas<->subject. This was achieved using the itkTransformReader and the a templated function over the image type and transform type to resample the images.



References

  • Magnotta VA, Heckel D, Andreasen NC, Cizadlo T, Corson PW, Ehrhardt JC, Yuh WT. "Measurement of brain structures with artificial neural networks: two- and three-dimensional applications", Radiology 211 (1999), 781-90.
  • Powell S, Magnotta VA, Johnson HJ, Jammalamadaka VK, Andreasen NC. "Registration and Machine Learning Based Automated Segmentation of Subcortical and Cerebellar Brain Structures", NeuroImage, In Press.
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