Simultaneous brain structures segmentation combining shape and pose forces

Authors:
Octavian Soldea;Trung Doan;Andrew Webb;Mark Van Buchem;Julien Milles;Radu Jasinschi
Affiliations:
Philips Research, Eindhoven, The Netherlands;Department of Radiology, Leiden University Medical Center, The Netherlands;CJ Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, The Netherlands;Department of Radiology, Leiden University Medical Center, The Netherlands;Department of Radiology, Leiden University Medical Center, The Netherlands;Philips Research, Eindhoven, The Netherlands
Venue:
MBIA'11 Proceedings of the First international conference on Multimodal brain image analysis
Year:
2011

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Abstract

This paper presents a new supervised learning based method for brain structure segmentation. We learn moment-based signatures of structures of interest and formulate the segmentation as a maximum a-posteriori estimation problem employing nonparametric multivariate kernel densities. For this problem, we propose a gradient flow solution. We have compared our method with state-of-the-art methods such as FSL-FIRST and Free-Surfer using volumetric 3T from IBSR. In addition, we have evaluated our algorithm on 7T MR data. We report comparative results of accuracy and significantly improved time-efficiency.