Traumatic Brain Injury (TBI) Detection

1. Traumatic Brain Injury (TBI) Detection Final Presentation –Winter 2012 Date: 18.05.2013 Presenters: Malihi Naveh, Fidelman Peli Project Advisor: Aides Amit Project Initiator: Dr. Nakhmani Arie

2. Motivation • TBI caused by an acute event • Severe damage to portions of the brain • TBI 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

3. 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

4. Literature survey • Main approaches for TBI detection: • Population based atlases • Symmetry based analysis • We chose the symmetry based approach • Doesn’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

5. Literature survey • Symmetry Analysis • Gabor8,10 • Edge matching • Flow vector8 • Energy medians comparison (boxing)11 • Methods fusion • Active 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 SPIEVol. 6789,.67891F, (2007). [6]  StivenSchwanz 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] ValentinaPedoia, ElisabettaBinaghi, Sergio Balbi, Alessandro De Benedictis, EmanueleMontiand 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] LiorDeutch & Marina Kokotov, “Sobolov Active Countours without edges”, a Student project in course “Introduction to Medicl Imaging”, Spring 2010.

6. Proposed solution PCA Symmetry Axis Gabor Edge Matching Symmetry affinity Empiric Threshold Thresholding Morphological Clustering Active Contours Contour 3D modeling 3D model

7. PCA Symmetry Axis Symmetry affinity Thresholding • Without Brain segmentation • Offset • Improvement Needed • Continued with manual Axis Clustering Contour 3D modeling

8. Gabor Symmetry Axis • Used As a BandPass • Gaussian size -> resolution • Circle shaped filter • Direction Variant • DC compensation Symmetry affinity Thresholding Clustering Contour 3D modeling

9. Gabor Symmetry Axis Symmetry affinity Thresholding Clustering Contour 3D modeling

10. Actual solution Manually Symmetry Axis Gabor Edge Matching Symmetry affinity Empiric Threshold Thresholding Morphological Clustering Active Contours Contour 3D modeling 3D model

11. Edge Detection Symmetry Axis • Bilateral Symmetry • Manual Axis • Used: Canny Edges Symmetry affinity Thresholding Clustering Contour 3D modeling

12. Edge Detection Symmetry Axis • Edges Flipped on each other • Later used: bwdist Symmetry affinity Thresholding Clustering Contour 3D modeling

13. Masking and Clustering Symmetry Axis • Skull removal • Elipse Shaped mask • Removal of small objects Symmetry affinity Thresholding Clustering Contour 3D modeling

14. Active Contour Symmetry Axis • Use initial detection edges as initial Snake. Symmetry affinity Thresholding Clustering Contour 3D modeling

15. Active Contour • Get final Contour using an active contour method. • Sobolev Snake Symmetry Axis Symmetry affinity Thresholding Click to See Movie Clustering Contour 3D modeling

16. Active Contour • Get final Contour using an active contour method. • Sobolev Snake Symmetry Axis Symmetry affinity Thresholding Clustering Contour 3D modeling

17. 3D modeling Symmetry Axis • Use 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 affinity Thresholding Clustering Contour 3D modeling

18. 3D modeling Symmetry Axis • Plot Blood Pools Using Patch: Symmetry affinity Thresholding Clustering Contour 3D modeling

19. Conclusions • A working Algorithm to detect Brain Blood Pools was presented. • Novelties in this work: • Symmetry Affinity Based on Edge comparison • 3D continuity conditions