1. NA-MIC National Alliance for Medical Image Computing http://na-mic.org Engineering a Segmentation Framework Marcel Prastawa

2. National Alliance for Medical Image Computing http://na-mic.org Need for Segmentation Applications Longitudinal analysis of growth Preprocessing for shape analysis Detect pathology Fully automatic, reproducible Allow fast prototyping Execute on hundreds of datasets

3. National Alliance for Medical Image Computing http://na-mic.org Our Method: Atlas-based Brain Segmentation T1T2TissueCortex

4. National Alliance for Medical Image Computing http://na-mic.org Quick Demo

5. National Alliance for Medical Image Computing http://na-mic.org Engineering Components Filtering Inhomogeneity Correction Affine Registration Deformable Registration Segmentation Statistics Pathology Atlas

6. National Alliance for Medical Image Computing http://na-mic.org Shared Components (EMSegment) Filtering Registration Inhomogeneity Correction Statistics Atlas Pathology

7. National Alliance for Medical Image Computing http://na-mic.org Future Components New modality / information –DTI –Vessels / MRA Pathology model –Tumor biomechanical model –Lesion model New classifiers

8. National Alliance for Medical Image Computing http://na-mic.org GUI vs Batch Mode GUI for prototyping Command line for batch processing: –Use automatically generated XML file –Different input images, same parameters –Python or shell scripts

9. National Alliance for Medical Image Computing http://na-mic.org Sample XML Input [1/2] EMS /scratch/prastawa/atlases/adult-atlas RAI /scratch/prastawa/test/out GIPL /scratch/prastawa/test/T1_Orig.nrrd ASR /scratch/prastawa/test/T2_Orig.nrrd ASR...

10. National Alliance for Medical Image Computing http://na-mic.org Sample XML Input [2/2]... 1 0.01 Curvature flow 4 1.2 1 0.7 1 5

11. National Alliance for Medical Image Computing http://na-mic.org Smart Execution Fast prototyping by storing results at different stages Examples: –Store registration transforms –Store estimated intensity distributions Write new results when input parameters changed

12. National Alliance for Medical Image Computing http://na-mic.org Tumor Segmentation T13DT2 T13DT2

13. National Alliance for Medical Image Computing http://na-mic.org Neonate Segmentation T1T23D T1 T2 3D

14. National Alliance for Medical Image Computing http://na-mic.org Lupus Lesion Segmentation T2 FLAIR 3D

15. National Alliance for Medical Image Computing http://na-mic.org Discussion Integrated system for registration, bias correction, segmentation Implemented using ITK classes Cross-platform: Linux, Windows, Solaris Smart execution: stored states Shared components Slicer integration?