2013 Summer Project Week:Epilepsy Surgery - Revision history

Murta at 15:01, 21 June 2013

2013-06-21T15:01:58Z

2013-06-21T14:48:20Z

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@@ Line 112: / Line 112: @@
 <li>As a nest step, I´ll integrate the code to 3DSlicer.
 <li>Try new schems of texture analisys to this application.
-<li>Implement few learning machine algorithms, in addition to image processing in C++.
+<li>Implement few machine learning algorithms, in addition to image processing in C++.
 <li>Speed up some time consumming algorithms with GPU programming.
 <li>Extend these and other ideas to cotical dysplasia: 2014 !

@@ Line 113: / Line 113: @@
 <li>Try new schems of texture analisys to this application.
 <li>Implement few learning machine algorithms, in addition to image processing in C++.
 <li>Extend these and other ideas to cotical dysplasia: 2014 !
 ==References==
 *Shaker, M. & Soltanian-Zadeh, H., 2008. Voxel-Based Morphometric Study of Brain Regions from Magnetic Resonance Images in Temporal Lobe Epilepsy. Image Analysis and Interpretation, 2008. SSIAI 2008. IEEE Southwest Symposium on, 209-212.

@@ Line 113: / Line 113: @@
 <li>Try new schems of texture analisys to this application.
 <li>Implement few learning machine algorithms, in addition to image processing in C++.
-<li>Extend these and other ideas to cotical dysplasia: next year !
+<li>Extend these and other ideas to cotical dysplasia: 2014 !
 ==References==
 *Shaker, M. & Soltanian-Zadeh, H., 2008. Voxel-Based Morphometric Study of Brain Regions from Magnetic Resonance Images in Temporal Lobe Epilepsy. Image Analysis and Interpretation, 2008. SSIAI 2008. IEEE Southwest Symposium on, 209-212.

@@ Line 113: / Line 113: @@
 <li>Try new schems of texture analisys to this application.
 <li>Implement few learning machine algorithms, in addition to image processing in C++.
-<li>Extend these idea to cotical dysplasia: next year!
+<li>Extend these and other ideas to cotical dysplasia: next year !
 ==References==
 *Shaker, M. & Soltanian-Zadeh, H., 2008. Voxel-Based Morphometric Study of Brain Regions from Magnetic Resonance Images in Temporal Lobe Epilepsy. Image Analysis and Interpretation, 2008. SSIAI 2008. IEEE Southwest Symposium on, 209-212.

@@ Line 105: / Line 105: @@
 <li>As a result, from preselected 32 texture feature descriptors, 6 were shown to be relevant for classification of TL tissues.
 <li>Thus, we observe that using approach of texture analysis of segmented images, can helps the specialist to identify signal change MRIs in the temporal lobes of patients with TLE.
 <li>Although these preliminary results are promising, the method still needs to be validated considering TL separatelly and in a larger image database.
@@ Line 111: / Line 112: @@
 <li>As a nest step, I´ll integrate the code to 3DSlicer.
 <li>Try new schems of texture analisys to this application.
 <li>Extend these idea to cotical dysplasia: next year!
 ==References==
 *Shaker, M. & Soltanian-Zadeh, H., 2008. Voxel-Based Morphometric Study of Brain Regions from Magnetic Resonance Images in Temporal Lobe Epilepsy. Image Analysis and Interpretation, 2008. SSIAI 2008. IEEE Southwest Symposium on, 209-212.

@@ Line 58: / Line 58: @@
 <b>Classifier</b>
 <li>Once segmented, the images are analyzed using texture descriptors from the intensity histogram and local pixels dependence measures proposed by Haralick were extracted.
-Subsequently, the set of feature vectors from the segmented images is evaluated using three classifiers in WEKA environment.
+Subsequently, the set of feature vectors from the segmented images is evaluated using three classifiers in [http://www.cs.waikato.ac.nz/ml/weka/ WEKA] environment.
 <li>Images of 32 patients with TLE were used, 15 of those exhibiting blurring phenomenon in TL and 17 do not.
 <li>In total, a set of 98 planar images was segmented, and 51 are classified in "with blurring" category and 47 "without blurring" category.

@@ Line 77: / Line 77: @@
 [[File:tlBlurred.png]]
 [[File:histBlurred.png]] blurring
+<br>
 <br>
 <b>Decision Tree</b>