2009 Winter Project Week StochasticTractography - Revision history

Jvs at 16:51, 16 December 2008

2008-12-16T16:51:20Z

Jvs at 16:41, 16 December 2008

2008-12-16T16:41:40Z

Jvs at 16:39, 16 December 2008

2008-12-16T16:39:12Z

Jvs at 14:14, 16 December 2008

2008-12-16T14:14:49Z

Jvs at 14:09, 16 December 2008

2008-12-16T14:09:52Z

Jvs at 14:08, 16 December 2008

2008-12-16T14:08:58Z

Jvs at 13:57, 16 December 2008

2008-12-16T13:57:59Z

Jvs at 13:56, 16 December 2008

2008-12-16T13:56:42Z

Dougt at 20:47, 8 December 2008

2008-12-08T20:47:48Z

Dougt at 20:47, 8 December 2008

2008-12-08T20:47:14Z

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 <h1>Objective</h1>
-Stochastic Tractography module has the ultimate goal to offer an estimation of the probability of white matter connection between two regions of the brain. For that, connectivity map is the fundamental output of the current algorithm implementation. It reveals given two regions the distribution of probability of connection per voxel.
+Stochastic Tractography module has the ultimate goal to offer an estimation of the probability of white matter connection between two regions of the brain. For that, connectivity map is the fundamental output of the current algorythm implementation. It reveals given two regions the distribution of probability of connection per voxel.
 </div>

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 ===Key Investigators===
-* BWH: Marek Kubicki, Julien von Siebenthal
+* BWH: Marek Kubicki, Julien de Siebenthal
 <div style="margin: 20px;">

← Older revision		Revision as of 16:39, 16 December 2008
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	<h1>Progress</h1>		<h1>Progress</h1>
−	The pipeline is implemented and ~~fully~~ functional. First test series show accurate adequacy between MatLAB and Python numerical computations of the Stochastic Tractography algorythm.	+	The pipeline is implemented and functional. First test series show accurate adequacy between MatLAB and Python numerical computations of the Stochastic Tractography algorythm. We would like during NAMIC integrate already existing Python wrapping of the Rician and Eddy current correction filters. An ideal wrapping solution for Slicer is indeed still to be defined. Moreover, we would like also during NAMIC to find out an EPI correction filter or if needed prototype a new one.

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 |[[Image:NAMIC-SLC.jpg|thumb|320px|Return to [[2009_Winter_Project_Week|Project Week Main Page]] ]]
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 |[[Image:NAMIC-SLC.jpg|thumb|320px|Return to [[2009_Winter_Project_Week|Project Week Main Page]] ]]
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← Older revision		Revision as of 13:57, 16 December 2008
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	<h1>Progress</h1>		<h1>Progress</h1>
−	The pipeline is implemented and fully functional. First test series show accurate adequacy between MatLAB and Python numerical computations of the ~~STochastic~~ Tractography algorythm.	+	The pipeline is implemented and fully functional. First test series show accurate adequacy between MatLAB and Python numerical computations of the Stochastic Tractography algorythm.

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 <h1>Objective</h1>
+Stochastic Tractography module has the ultimate goal to offer an estimation of the probability of white matter connection between two regions of the brain. For that, connectivity map is the fundamental output of the current algorithm implementation. It reveals given two regions the distribution of probability of connection per voxel.
 </div>
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 <h1>Approach, Plan</h1>
+A complete pipeline implementation was forseen in order to give to the researcher the best access to the different features Stochastic Tractography can offer. Based on the MatLAB implementation and constantly compared to it, a Python integration was devised. It offers as a proof of concept the possibility to directly prototype an algorithm with direct integration into the Slicer solution without using MatLAB. This should alleviate issues related to code translation from MatLAB to Slicer.
 </div>
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 <h1>Progress</h1>
+The pipeline is implemented and fully functional. First test series show accurate adequacy between MatLAB and Python numerical computations of the STochastic Tractography algorythm.

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 ===References===
-*([http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Bjornemo et al., 2002])
+* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
-:* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
+* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
-:* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
+* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]