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

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<h1>Progress</h1>
 
<h1>Progress</h1>
  
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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===References===
 
===References===
* 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.
* 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.
* 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
 
* 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 .
 

Revision as of 00:59, 25 June 2007

Home < Collaboration < Iowa < Meshing < Migrate Iowa Neural Net code to pure ITK

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




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.