""" ================================== BUAN Bundle Shape Similarity Score ================================== This example explains how we can use BUAN [Chandio2020]_ to calculate shape similarity between two given bundles. Where, shape similarity score of 1 means two bundles are extremely close in shape and 0 implies no shape similarity whatsoever. Shape similarity score can be used to compare populations or individuals. It can also serve as a quality assurance metric, to validate streamline registration quality, bundle extraction quality by calculating output with a reference bundle or other issues with pre-processing by calculating shape dissimilarity with a reference bundle. First import the necessary modules. """ import numpy as np from dipy.viz import window, actor from dipy.segment.bundles import bundle_shape_similarity from dipy.segment.bundles import select_random_set_of_streamlines from dipy.data import two_cingulum_bundles """ To show the concept we will use two pre-saved cingulum bundle. Let's start by fetching the data. """ cb_subj1, _ = two_cingulum_bundles() """ Let's create two streamline sets (bundles) from same bundle cb_subj1 by randomly selecting 60 streamlines two times. """ rng = np.random.RandomState() bundle1 = select_random_set_of_streamlines(cb_subj1, 60, rng=None) bundle2 = select_random_set_of_streamlines(cb_subj1, 60, rng=None) """ Now, let's visualize two bundles. """ def show_both_bundles(bundles, colors=None, show=True, fname=None): scene = window.Scene() scene.SetBackground(1., 1, 1) for (i, bundle) in enumerate(bundles): color = colors[i] streamtube_actor = actor.streamtube(bundle, color, linewidth=0.3) streamtube_actor.RotateX(-90) streamtube_actor.RotateZ(90) scene.add(streamtube_actor) if show: window.show(scene) if fname is not None: window.record(scene, n_frames=1, out_path=fname, size=(900, 900)) show_both_bundles([bundle1, bundle2], colors=[(1, 0, 0), (0, 1, 0)], show=False, fname="two_bundles.png") """ .. figure:: two_bundles.png :align: center Two Cingulum Bundles. """ """ Calculate shape similarity score between two bundles. """ """ 0 cluster_thr because we want to use all streamlines and not the centroids of clusters. """ clust_thr = [0] """ Threshold indicates how strictly we want two bundles to be similar in shape. """ threshold = 5 ba_score = bundle_shape_similarity(bundle1, bundle2, rng, clust_thr, threshold) print("Shape similarity score = ", ba_score) """ Let's change the value of threshold to 10. """ threshold = 10 ba_score = bundle_shape_similarity(bundle1, bundle2, rng, clust_thr, threshold) print("Shape similarity score = ", ba_score) """ Higher value of threshold gives us higher shape similarity score as it is more lenient. """ """ References ---------- .. [Chandio2020] Chandio, B.Q., Risacher, S.L., Pestilli, F., Bullock, D., Yeh, FC., Koudoro, S., Rokem, A., Harezlak, J., and Garyfallidis, E. Bundle analytics, a computational framework for investigating the shapes and profiles of brain pathways across populations. Sci Rep 10, 17149 (2020) """