1. http://www.rad.upenn.edu/sbia Medical Image Analysis @ SBIA.UPenn Christos Davatzikos Director, Section of Biomedical Image Analysis Professor, Radiology, ESE, BE University of Pennsylvania

2. http://www.rad.upenn.edu/sbia

3. Clinical studies Techniques Human brain imaging: AD/aging, Schizophrenia Treatment of Diabetes Effects of hormonal and environmental exposures to the brain Effects of alcohol Treatment planning: Brain tumors Optimized prostate biopsy Animal imaging: DTI of the developing mouse brain Hormonal effects on Monkey brain development Breast MRI Cardiac image analysis, FMRI post- processing Hi-D Pattern classification as diagnostic tool Facial expression analysis for affective disorders Segmentation and labeling Spatial normalization/ registration Morphological analysis Image statistics and data- mining Biomechanical Biophysical modeling

4. Segmentation and Labeling Prostate segmentation Spine segmentation Hippocampal segmentation Problem definition Automated segmentation of anatomical structures from the images of different modalities, for quantitative comparison and shape analysis. Motivation Volumetric measurement of anatomical structures. Longitudinal comparison, revealing disease-related changes. Group comparison of healthy controls and patients. Examples Sulcal labeling

5. Problem definition Image data co-registration and integration, from different individuals, modalities, times, and conditions, for comparative image analysis such as characterization of structural, functional variability and abnormality. Motivation Group comparison, by computing inter-individual variability. Longitudinal comparison, for measuring diseases, i.e. AD. Longitudinal follow-up, with/without treatment. Different modalities integration, for conveying complementary information. Spatial normalization and registration Warping of subject to model

6. Model Measuring volumes of anatomical structures : An atlas with anatomical definitions is registered to the patient’s images Subject HAMMER

7. Distribution of HAMMER (6/21/2008)

8. Year 1 Year 2 Year 3 Year 4 Original Images 3-D Seg- mentation CLASSIC 4-D Segm- entation 4-Dimensional Image Analysis for Measurement of Temporal Changes

9. Pattern Classification Abnormality score Multi-parametric Pattern Classification

10. Data from ADNI AD vs CN classifier applied to MCI: most MCI’s have AD-like MRI profiles Subsequent cognitive decline

11. Segmentation of Brain Lesions threshold = -1 Manual definition threshold = 0threshold = 2 FLAIR

13. Diffusion Tensor Imaging: Manifold-based Statistical Analysis B0 image and at least 6 gradient directions/slice Reconstructed DTI Multi-parametric Information Geodesic-based and Kernel- based Statistics Schizophrenia patients Vs Controls Developing mouse brain : old Vs young

14. Thank you