In the next step, we need to make sure that all the streamlines in each bundle are oriented the same way. For example, for the CST, we want to make sure that all the bundles have their cortical termination at one end of the streamline. This is that when we later extract values from a volume, we won't have different streamlines going in opposite directions. To orient all the streamlines in each bundles, we will create standard streamlines, by finding the centroids of the left AF and CST bundle models. The advantage of using the model bundles is that we can use the same standard for different subjects, which means that we'll get roughly the same orientation """ import dipy.data as dpd from dipy.data.fetcher import get_two_hcp842_bundles model_af_l_file, model_cst_l_file = get_two_hcp842_bundles() model_af_l, hdr = load_trk(model_af_l_file) model_cst_l, hdr = load_trk(model_cst_l_file) from dipy.segment.metric import (AveragePointwiseEuclideanMetric, ResampleFeature) from dipy.segment.clustering import QuickBundles feature = ResampleFeature(nb_points=100) metric = AveragePointwiseEuclideanMetric(feature) """ Since we are going to include all of the streamlines in the single cluster from the streamlines, we set the threshold to `np.inf`. We pull out the
size=(600, 600)) if interactive: window.show(ren) """ .. figure:: tractograms_after_registration.png :align: center Atlas and target after registration. """ """ Read AF left and CST left bundles from already fetched atlas data to use them as model bundles """ model_af_l_file, model_cst_l_file = get_two_hcp842_bundles() """ Extracting bundles using recobundles [Garyfallidis17]_ """ sft_af_l = load_trk(model_af_l_file, "same", bbox_valid_check=False) model_af_l = sft_af_l.streamlines rb = RecoBundles(moved, verbose=True) recognized_af_l, af_l_labels = rb.recognize(model_bundle=model_af_l, model_clust_thr=5., reduction_thr=10, reduction_distance='mam', slr=True, slr_metric='asymmetric',
if interactive: window.show(ren) """ .. figure:: tractograms_after_registration.png :align: center Atlas and target after registration. """ """ Read AF left and CST left bundles from already fetched atlas data to use them as model bundles """ from dipy.data.fetcher import get_two_hcp842_bundles bundle1, bundle2 = get_two_hcp842_bundles() """ Extracting bundles using recobundles [Garyfallidis17]_ """ model_bundle, _ = load_trk(bundle1) rb = RecoBundles(moved, verbose=True) recognized_bundle, rec_labels = rb.recognize(model_bundle=model_bundle, model_clust_thr=5., reduction_thr=10, reduction_distance='mam', slr=True, slr_metric='asymmetric', pruning_distance='mam')