1. Fast Intra- and Intermodal Deformable Registration Based on Local Subvolume Matching Matthias Söhn 1, Verena Scheel 2, Markus Alber 1 (1) Radiooncological Clinic, Section for Biomedical Physics, University of Tübingen, Germany (2) Laboratory for Preclinical Imaging and Imaging Technology, Department of Radiology, University of Tübingen, Germany Forschungszentrum für Hochpräzisionsbetrahlung

2. 2 ESTRO 2007 Barcelona – Söhn et al. UKTübingen Deformable Registration for Radiotherapy Requirements & Challenges: accuracy fast no or little user interaction versatility 4D-CT CT-ConeBeamCT CT-MRI Featurelet-based deformable registration our approach…

3. 3 ESTRO 2007 Barcelona – Söhn et al. UKTübingen Algorithmic Implementation 1 Cover region of interest in reference image with regular 3D-grid of featurelets typical size: 1.5x1.5x1.5 cm

4. 4 ESTRO 2007 Barcelona – Söhn et al. UKTübingen reference image (exhale) target image (inhale) 2 for each featurelet Individual rigid registration of each featurelet maximization of local normalized mutual information (NMI) allowing 3D-shifts within local search region  fast & parallelizable!

5. 5 ESTRO 2007 Barcelona – Söhn et al. UKTübingen reference image (exhale) target image (inhale) 2 regions with mismatched featurelets Individual rigid registration of each featurelet for each featurelet maximization of local normalized mutual information (NMI) allowing 3D-shifts within local search region  fast & parallelizable!

6. 6 ESTRO 2007 Barcelona – Söhn et al. UKTübingen Automatic assessment of local registration quality 3 reference featurelet registered target featurelet local similarity measure field (NMI) accept position => shift to position with minimal local deformation energy => …shift to position with minimal local deformation energy within NMI-optimum =>

7. 7 ESTRO 2007 Barcelona – Söhn et al. UKTübingen Automatic assessment of local registration quality -- Result 3

8. 8 ESTRO 2007 Barcelona – Söhn et al. UKTübingen Relaxation Step: Iterative Minimization of Deformation Energy for mismatched Featurelets 4

9. 9 ESTRO 2007 Barcelona – Söhn et al. UKTübingen B-Spline Interpolation of Featurelet shift vectors 5 target image, final featurelet positions interpolation of shift vectors => continuous deformation field!

10. 10 ESTRO 2007 Barcelona – Söhn et al. UKTübingenResults RCCT Inhale-Exhale deformable registration: Visual evaluation before……after registration

11. 11 ESTRO 2007 Barcelona – Söhn et al. UKTübingenResults CT-ConeBeamCT deformable registration: Visual evaluation Elekta XVI ConeBeam-CT data, courtesy D. Yan, Y. Chi (Beaumont) before… …after registration

12. 12 ESTRO 2007 Barcelona – Söhn et al. UKTübingenResults CT-MRI deformable registration: Visual evaluation before… …after registration CT MRIMRI (backtransformed)

13. 13 ESTRO 2007 Barcelona – Söhn et al. UKTübingenResults Quantitative evaluation: Anatomical landmarks N 3D-residuals [mm]… before registration after registration pat. 1158.2±4.61.3±0.9 pat. 2114.2±1.51.5±1.0 pat. 31410.4±5.51.8±0.7 pat. 4157.8±5.71.8±1.3 avg. 7.8±5.1 (max. 21.3) 1.6±1.0 (max. 4.6) N=55 landmarks altogether marked in inhale and exhale CTs of 4 patients [Siemens Somatom Sensation Open RCCT datasets @ 1x1x3mm voxelsize]

14. 14 ESTRO 2007 Barcelona – Söhn et al. UKTübingenResults Quantitative evaluation: Virtual phantom courtesy D. Yan, Y. Chi (Beaumont Hospital) Virtual thorax phantom: known deformation field used to to deform real lung CT dataset [based on ~740.000 voxels] before: 2.9±2.8mm after: 1.1±1.2mm Residuals of featurelet algorithm based on thorax phantom:

15. 15 ESTRO 2007 Barcelona – Söhn et al. UKTübingenResults Computational performance test case registered region [voxels] calculation time (dual-core Xeon PC, 2x2.66GHz) Thorax (CT-CT)360x270x1202min 12sec H&N (CT-CBCT)225x225x11549sec H&N (CT-MRI)378x210x701min 23sec calculation time mainly depends on… size of registered region size of local search region featurelet size

16. 16 ESTRO 2007 Barcelona – Söhn et al. UKTübingenResults Computational performance test case registered region [voxels] calculation time (dual-quadcore Xeon PC, 8x2.66GHz) Thorax (CT-CT)360x270x12038sec H&N (CT-CBCT)225x225x11514sec H&N (CT-MRI)378x210x7019sec “online” deformable registration!

17. 17 ESTRO 2007 Barcelona – Söhn et al. UKTübingenConclusions Featurelet-based deformable registration: fast, parallizable model-independent, fully automatic enables multi-modality registration due to use of mutual information sub-voxel registration accuracy as shown by landmark-based evaluation and virtual thorax phantom ‘online’ multi-modality deformable registration within reach!