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Traumatic Brain Injury (TBI) DetectionFinal Presentation –Winter 2012
Date: 18.05.2013Presenters: Malihi Naveh, Fidelman PeliProject Advisor: Aides AmitProject Initiator: Dr. Nakhmani Arie
Motivation
TBI caused by an acute eventSevere damage to portions of the brainTBI may cause severe disabilities -
cognitive deflects, communication, mental health.
1.7 million new cases of TBI in the U.S. each year
50,000 deaths caused by TBI each year in the U.S.
Need for automatic tools for TBI clinical practice and patient monitoring
MRI Imaging
Magnetic Resonance Imaging (MRI)A medical imaging technique used in radiology
to visualize internal structures of the body Good contrast between the different soft
tissues of the body
MRI uses non-ionizing radiation (unlike CT)
Different types of MRI scans: MP_RAGE, FLAIR, T1-weighted etc.
Expansive
Literature survey
Main approaches for TBI detection: Population based atlasesSymmetry based analysis
We chose the symmetry based approachDoesn’t require statistical analysis of large data
bases More robust – age & population independent
Symmetry Axis detection:Preprocessing – brain segmentation3
PCA – Principal Component Analysis1,5
PSD – Phase Based Symmetry detection1
Gravitational torque4
Literature survey
Symmetry Analysis Gabor8,10
Edge matchingFlow vector8
Energy medians comparison (boxing)11
Methods fusionActive Contours12
[1] http://en.wikipedia.org/wiki/Magnetic_resonance_imaging#Other_specialized_MRI_techniques[2] http://www.na-mic.org/Wiki/index.php/DBP3:UCLA#What_is_traumatic_brain_injury.3F[3] L. Smith, A Tutorial on Principal Components Analysis, www.cs.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf, 2002.[4] Zhito Xiao and Hun Wu, “Analysis on Image Symmetry Detection Algorithms”, (FSKD 2007. V.4, pp 745-750. [5] E Song ,et al, ” Symmetry analysis to detect pathological brain in MRI”, MIPPR 2007. Proc. of SPIE Vol. 6789,.67891F, (2007).[6] Stiven Schwanz Dias, “Improved 2D Gabor filter”, Matlab Central – File exchange, http://www.mathworks.com/matlabcentral/fileexchange/13776-improved-2d-gabor-filter.[7] H. Khotanlou, O. Colliot, I. Bloch, “Automatic brain tumor segmentation using symmetry analysis and deformable models”, in: Internat. Conf. on Advances in Pattern Recognition ICAPR, Kolkata, India, January 2007.[8] Y. Sun, B. Bhanu, and S. Bhanu, “Automatic Symmetry-Integrated Brain Injury Detection in MRI Sequences”, Proc. IEEE CS Conf. Computer Vision and Pattern Recognition Workshop, 2009.[9] Valentina Pedoia, Elisabetta Binaghi, Sergio Balbi, Alessandro De Benedictis, Emanuele Monti and Renzo Minotto, "Glial brain tumor detection by using symmetry analysis", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 831445 (February 23, 2012); doi:10.1117/12.910172; http://dx.doi.org/10.1117/12.910172.[10] J. Movellan, “Tutorial on Gabor Filters”, technical report, MPLab Tutorials, Univ. of California, San Diego, 2005. [11] N. Ray, R. Greiner and A. Murtha, “Using Symmetry to Detect Abnormalities in Brain MRI”, Computer Society of India Communications, 31(19), pp 7-10, 2008. [12] Lior Deutch & Marina Kokotov, “Sobolov Active Countours without edges”, a Student project in course “Introduction to Medicl Imaging”, Spring 2010.
Proposed solutionPCA
Gabor Edge Matching
Symmetry Axis
Symmetry affinity
Thresholding
Clustering
Contour
Empiric Threshol
d
Morphological
Active Contours
3D modeling3D model
PCASymmetry
Axis
Symmetry affinity
Thresholding
Clustering
Contour
gray scale image, 2D calc -frame 1 Binary image, 2D calc. Err=7.65 deg- frame 1 gray scale image, 3D calc. Err=9.36 deg- frame 1
Without Brain segmentationOffset
Improvement NeededContinued with manual Axis
3D modeling
Gabor
Used As a BandPassGaussian size -> resolution
Circle shaped filterDirection VariantDC compensation
2 2
2 2
11
0.5
ln 0.5 0.7
0.470.47[ ]
S R
R cm
e
S R
S S cmR
Symmetry Axis
Symmetry affinity
Thresholding
Clustering
Contour
3D modeling
GaborLeft hemisphere Flipped Right hemisphere
Left Right Diffrence
1
1
1
201
40
S pixels
F pixels
Symmetry Axis
Symmetry affinity
Thresholding
Clustering
Contour
3D modeling
Actual solutionManually
Gabor Edge Matching
Symmetry Axis
Symmetry affinity
Thresholding
Clustering
Contour
Empiric Threshol
d
Morphological
Active Contours
3D modeling3D model
Edge DetectionBilateral SymmetryManual AxisUsed: Canny Edges
Original Scan
50 100 150 200 250
50
100
150
200
250
Edge detection
Symmetry Axis
Symmetry affinity
Thresholding
Clustering
Contour
3D modeling
Edge DetectionEdges Flipped on each otherLater used: bwdist
Left edge Right edgeCombined edges:
Left, Right, Overlap - Red, Green,Blue
Symmetry Axis
Symmetry affinity
Thresholding
Clustering
Contour
3D modeling
Masking and ClusteringSkull removal
Elipse Shaped maskRemoval of small objects
Distance between Edges Thresholding Removal of small objects
2 2
1c cX X Y Y
a b
Symmetry Axis
Symmetry affinity
Thresholding
Clustering
Contour
3D modeling
Active ContourUse initial detection edges as
initial Snake.
Symmetry Axis
Symmetry affinity
Thresholding
Clustering
Contour
3D modeling
Original Scan
50 100 150 200 250
50
100
150
200
250
Active ContourSymmetry
Axis
Symmetry affinity
Thresholding
Clustering
Contour
3D modeling
Get final Contour using an active contour method.Sobolev Snake
Click toSee
Movie
Active ContourSymmetry
Axis
Symmetry affinity
Thresholding
Clustering
Contour
3D modeling
Get final Contour using an active contour method.Sobolev Snake
Original Scan
50 100 150 200 250
50
100
150
200
250
3D modelingUse Snakes from different
frames as initial 3d data. Apply continuity conditions.Smoothing the data using 3d
gaussian. Determine blood pool surface in
3d space.
Symmetry Axis
Symmetry affinity
Thresholding
Clustering
Contour
3D modeling
3D modelingPlot Blood Pools Using Patch:
Symmetry Axis
Symmetry affinity
Thresholding
Clustering
Contour
3D modeling
Conclusions
A working Algorithm to detect Brain Blood Pools was presented.
Novelties in this work:Symmetry Affinity Based on Edge
comparison3D continuity conditions
