Reformatting registration Fiducials segmentation registration dataset1 dataset2 dataset1 dataset2 transformation reformatted dataset transformation reformatted.

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Presentation transcript:

reformatting registration Fiducials segmentation registration dataset1 dataset2 dataset1 dataset2 transformation reformatted dataset transformation reformatted dataset Fiducials-based Registration methods Iconic Registration methods FIGURE 1.

call registration Selection of datasets to register WorkstationRegistration server FIGURE 2. :Example MR / PET registration Calculation of Geometric transformation return geometric transformation Dataset reformatting CASE 1 CASE 2 Display call registration Selection of datasets to register Calculation of Geometric transformation return reformatted datasetDataset reformatting Display

call registration (transfo object -> target) Selection of dataset to register WorkstationRegistration server (e.g. SPM) FIGURE 3. : Example MR / MR template registration (anatomical standardization of fMRI data) Calculation of Geometric transformation return geometric transformation (12 param affine transform + nonlinear transform) Apply transfo To fMRI image series CASE 1 CASE 2 Statistical analysis call registration (compute and apply transfo) Selection of datasets to register Calculation of Geometric transformation return reformatted datasets Apply transfo To fMRI image series Statistical analysis

call registration Detection of skin in MR WorkstationRegistration server (e.g. SPM) FIGURE 4. : Example headshape / MR registration (e.g. MEG/EEG / MR) Surface-based Registration return geometric transformation (rigid transform) Visual Control of accuracy CASE 1 CASE 2 call registration (feature extraction + surface matching) Selection of datasets to register return geometric transformation (rigid transform) Selection of datasets to register Visual Control of accuracy Detection of skin in MR Surface-based Registration

Definition Of fiducials Registration Server Neuronavigation workstation FIGURE 5: Example pre-op images / intra-op images registration (e.g. neuronavigation) Fiducials-based Registration (patient, Pre-op images) Call registration (intra-op images –> pre_op images) Acquisition of intra- op images (e.g. US) Apply transfo To match pre-op data with intra-op data Return non-linear transfo Compute Non-linear transfo