Section: New Results

A Prototype Representation to Approximate White Matter Bundles with Weighted Currents

Participants : Pietro Gori [correspondant] , Olivier Colliot, Linda Marrakchi-Kacem, Fabrizio de Vico Fallani, Mario Chavez, Sophie Lecomte, Cyril Poupon, Andreas Hartmann, Nicholas Ayache, Stanley Durrleman.

Quantitative and qualitative analysis of white matter fibers resulting from tractography algorithms is made difficult by their huge number. To this end, we propose an approximation scheme which gives as result a more concise but at the same time exhaustive representation of a fiber bundle. It is based on a novel computational model for fibers, called weighted currents, characterized by a metric that considers both the pathway and the anatomical locations of the endpoints of the fibers. Similarity has therefore a twofold connotation: geometrical and related to the connectivity. The core idea is to use this metric for approximating a fiber bundle with a set of weighted prototypes, chosen among the fibers, which represent ensembles of similar fibers. The weights are related to the number of fibers represented by the prototypes. The algorithm is divided into two steps. First, the main modes of the fiber bundle are detected using a modularity based clustering algorithm. Second, a prototype fiber selection process is carried on in each cluster separately. This permits to explain the main patterns of the fiber bundle in a fast and accurate way. See Fig. 3

Figure 3. Illustration of our method to cluster fibers and approximate clusters based on a weighted currents metric, which measures differences in the locations of fibers extremities and the geometry of their pathway. 2 examples are shown using fibers from a deterministic tractography (left) and probabilistic tractography (right). Clustering (top row) and approximation of fibers within each cluster (bottom row) are shown.

More details in [24] .