Abstract #0038

Reducing false positives in tractography with microstructural and anatomical priors

Alessandro Daducci^1,2,3, Muhamed Barakovic², Gabriel Girard², Maxime Descoteaux^4,5, and Jean-Philippe Thiran^2,3

¹Computer Science department, University of Verona, Verona, Italy, ²Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland, ³Radiology department, University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, ⁴Sherbrooke Connectivity Imaging Laboratory (SCIL), University of Sherbrooke, Sherbrooke, QC, Canada, ⁵Department of Nuclear Medicine and Radiobiology, Faculty of Medicine and Health Science, Sherbrooke Molecular Imaging Center, Sherbrooke, QC, Canada

Tractography has proven particularly effective for studying noninvasively the neuronal architecture of the brain but recent studies have showed that the high incidence of false positives can significantly bias any connectivity analysis. We present a novel processing framework that can dramatically reduce these false positives, i.e. improving specificity, without affecting the sensitivity, by considering two very basic observations about white-matter anatomy. Our results may have profound implications for the use of tractography to study brain connectivity.

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