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Abstract #4301

Connectoflow: A cutting-edge Nextflow pipeline for structural connectomics

Francois Rheault1,2, Jean-Christophe Houde2, Jasmeen Sidhu3, Sami Obaid2,4, Guido Guberman5, Alessandro Daducci6, and Maxime Descoteaux2
1Electrical Engineering, Vanderbilt University, Nashville, TN, United States, 2Computer Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada, 3Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada, 4Centre de Recherche du Centre Hospitalier, Université de Montréal, Montréal, QC, Canada, 5Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada, 6Computer Science, University of Verona, Verona, Italy

Tractography involves complicated processing and connectomics include even more complexity. To facilitate structural connectome reconstruction we present: Connectoflow. Connectoflow requires simple inputs, has simple options and provides simple outputs, all with cutting-edge processing. By leveraging the simplicity of Nextflow and Docker/Singularity, Connectoflow is robust and efficient. By combining Tractoflow with Connectoflow, one can go from raw DW-images to structural connectomes in a few simplified steps. The proposed pipeline innovates by including connection-wise cleaning/filtering, provides connection weights that go beyond streamline count (COMMIT) as well as advanced connection-wise metrics (similarity and AFD).

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