Work

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

Year: 2014

Type: conference-paper

Abstract: 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.

Source: IEEE International Symposium on Biomedical Imaging (ISBI)

DOI: 10.1109/isbi.2014.6867976

Authors: Oscar Esteban, Alessandro Daducci, Emmanuel Caruyer, Kieran O'Brien, Maria J. Ledesma-Carbayo, Meritxell Bach-Cuadra, Andres Santos

Institutions: École Polytechnique Fédérale de Lausanne, Universidad Politécnica de Madrid, University of Pennsylvania, University of Geneva, University of Lausanne

Language: English

Topic: Advanced Neuroimaging Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W2148316870

FWCI: 7.798

Cites: 12

Cited by: 16

Related to: 10