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Abstract #2878

Optimizing N3 Parameters Leads to Better Segmentation Accuracy on 3T Scanners

Weili Zheng1, Michael WL Chee2, Vitali Zagorodnov1

1Computer Engineering, Nanyang Technological University, Singapore, Singapore; 2Cognitive Neuroscience Laboratory, Duke-NUS Graduate Medical School, Singapore, Singapore


A recent study by Boyes at al. have found that performance of non-parametric nonuniformity correction approach N3 on 3T scanners could be improved by reducing the value of the parameter that controls the smoothness of the estimated bias field. The present study not only confirms this finding but also demonstrates the benefits of using smaller smoothing distances (30-50mm compared with default 200mm) on the quality of white matter surface estimation and reliability of cortical thickness and subcortical structures volumes, which is promising to increase the feasibility of longitudinal neurological studies.