Difference between revisions of "2017 Winter Project Week/MeningiomaSegmentation"

Revision as of 01:11, 13 January 2017

Home < 2017 Winter Project Week < MeningiomaSegmentation

Objective	Approach and Plan	Progress and Next Steps
Segment meningiomas in structural MR images. Assess state of brain after surgical removal of meningioma.	Evaluate performance of existing segmentation methods.	Progress Segmented with ANTs and FSL. Learned about Slicer segmentation tools, and segmented semi-automatically. Put in contact with people who have segmented meningiomas. Next steps Continue learning about what has been done in the past. Improve brain-extraction. Continue testing existing segmentation methods. Try Slicer in a Nipype workflow. Apply manifold learning (a method of dimensionality reduction).

MR images of meningiomas that will be used in this project are available at OpenNeu.ro.

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 Image:PW-Winter2017.png|link=2017_Winter_Project_Week#Projects|[[2017_Winter_Project_Week#Projects|Projects List]]
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+Image:Jk_meningioma_seg.png|link=File:Jk_meningioma_seg.png|[[Jk_meningioma_seg.png|Meningioma Segmentation]]
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 <!-- Progress and Next steps bullet points (fill out at the end of project week) -->
-*
+Progress
+* Segmented with ANTs and FSL.
+* Learned about Slicer segmentation tools, and segmented semi-automatically.
+* Put in contact with people who have segmented meningiomas.
+Next steps
+* Continue learning about what has been done in the past.
+* Improve brain-extraction.
+* Continue testing existing segmentation methods.
+* Try Slicer in a Nipype workflow.
+* Apply manifold learning (a method of dimensionality reduction).
 |}