Simulation-based evaluation of susceptibility distortion correction methods in diffusion MRI for connectivity analysis

• Presented at: IEEE 11th International Symposium on Biomedical Imaging - From Nano to Macro (ISBI), Beijing, China, April 29 - May 2, 2014
• Publication date: 2014

Connectivity analysis on diffusion MRI data of the whole- brain suffers from distortions caused by the standard echo- planar imaging acquisition strategies. These images show characteristic geometrical deformations and signal destruction that are an important drawback limiting the success of tractography algorithms. Several retrospective correction techniques are readily available. In this work, we use a digital phantom designed for the evaluation of connectivity pipelines. We subject the phantom to a “theoretically correct” and plausible deformation that resembles the artifact under investigation. We correct data back, with three standard methodologies (namely fieldmap-based, reversed encoding-based, and registration- based). Finally, we rank the methods based on their geometrical accuracy, the dropout compensation, and their impact on the resulting connectivity matrices.

Keywords: LTS5 ; Diffusion MRI ; Brain connectivity ; Distortion correction ; CIBM-SPC

Reference

• EPFL-CONF-196964

Record created on 2014-02-19, modified on 2017-05-10