1. Invariant SPHARM Shape Descriptors for Complex Geometry in MR Region of Interest Analysis Ashish Uthama 1 Rafeef Abugharbieh 1 Anthony Traboulsee 2 Martin J. McKeown 1,2 Presented by Bernard Ng 1 1 Biomedical Signal and Image Computing Laboratory, Department of ECE, University of British Columbia 2 Department of Medicine, University of British Columbia

2. Overview Introduction Shape analysis using ROIs in MR Current analysis techniques Background Our earlier SPHARM approach New SPHARM approach proposed Method Feature extraction Feature analysis Validation Results Shape Analysis of the thalamus in PD

3. Shape Analysis Using ROIs in MR High resolution structural MR helps in studying deep brain structures Most neurological disease effect the integrity of brain structures (PD, MS, etc) In some diseases this effect could be a systematic change in shape Using ROI (Region of Interest) based shape analysis helps study these changes locally Introduction Background Method Results 3 Manually traced Region of Interests (ROI) delineating the left and right thalamus for further shape analysis

4. Current Analysis Techniques Voxel count to represent volume  Very simplistic measure  Does not capture shape Template based representation (medial, atlas, etc)  Most require manual selection of Land Marks  Requires mutual registration Automated feature extraction  Limited to spherical topology Introduction Background Method Results 4

5. Our Earlier SPHARM Approach Scale, rotation and translation invariant No mutual registration Insensitive to subject (ROI) orientation or brain size ROI surface represented as a function of distance from the centre of mass Thus limited to ROIs without self occlusions Introduction Background Method Results 5 A limitation for potential future work on arbitrarily complex ROIs (e.g MS leison shape etc) Cross sections of hypothetical 3D volumes r

6. New SPHARM Approach Proposed Based on representing the ROI volume using concentric spherical shells Arbitrarily shaped ROIs can be analyzed Earlier such representations were not unique Novel implementation of a radial transform Ensures unique feature vectors Introduction Background Method Results 6

7. Feature Extraction 1 B A C A BC Determine the maximum radius R max (in voxels) Obtain the bandwidth (L) Obtain 2R max number of shells with radius equally spaced between 1 and R i, Intersect these shells with the binary ROI mask, interpolating as required Introduction Background Method Results 7

8. Feature Extraction 2 Obtain the basic SPHARM representation for each shell To obtain unique representation under independent rotations of the ROI section contained in each shell, use a radial transform Obtain the final invariants Introduction Background Method Results 8 L L L L Shell 1 Shell rShell 2R max …… c m 1l c m rl c m 2R max l c m 1l c m rl c m 2R max l............ Radial transform c m 1l c m kl c m 2R max l............

9. Feature Analysis Obtain features for both groups (e.g. PD vs. Healthy controls) Reshape each feature into a vector Use a permutation test to determine if the two groups have a significant difference Does not need a generating probability distribution Best suited for long feature vectors seen in biomedical applications Introduction Background Method Results 9

10. Validation Two groups with 20 3D ellipsoidal volumes each were generated using: Realistic intersubject variability was introduced by:  Random shifts of the centroid  Random rotations about all 3 axes  Gaussian noise on the surface With fixed a and b, c was varied over a range to study the performance of the method Introduction Background Method Results 10 (a) Real data (b) and (c) are the two synthetic groups created As the graph approaches c b =10 the group difference in shape reduces

11. Shape Analysis of the PD Thalami 21 controls and 19 PD patients were scanned twice. Once before and once two hours after the administration of a drug Rmax for both thalamus was found to be 20 voxels, 40 shells with a bandwidth of 36 were used Obtained feature length was 1440 Pre and Post drug analysis yielded no significance Significant differences observed in both the left and the right thalamus between healthy controls and PD Introduction Background Method Results 11

12. Conclusion SPHARM based invariant feature vectors for a 3D volume Unique radial transform to obtain unique vectors Validated with synthetic data Application to real data Significant shape changes were observed in addition to volumetric changes indicating that atrophy is not isotropic Introduction Background Method Results 12

13. Questions and Comments ashishu@ece.ubc.ca