Joint fMRI brain activation detection and segmentation using level sets

• Published in: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Vol. 2010; pp. 5708 - 5711
• Main Authors: Silveira, M, Figueiredo, P
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.01.2010
• Subjects: Analytical models; Brain Mapping - methods; Brain modeling; Data models; Humans; Image Interpretation, Computer-Assisted - methods; Imaging; Level set; Magnetic Resonance Imaging - methods; Motor Activity - physiology; Phantoms, Imaging; Photic Stimulation; Reproducibility of Results; Task Performance and Analysis; Three dimensional displays; Visualization
• ISBN: 1424441234; 9781424441235
• ISSN: 1094-687X; 1557-170X
• DOI: 10.1109/IEMBS.2010.5627878

This paper proposes a parametric, multivariate method for the joint detection and segmentation of brain activation based on fMRI data. The proposed technique uses region based level sets to separate between the task-related and non-task-related regions and performs, at each iteration of level set evolution, a separate multivariate linear model (MLM) analysis in each of the two regions. Simulations using synthetic data generated based on typical experimental parameters and noise levels showed a false positive rate of 6% and a false negative rate of 2% for the results obtained with the proposed technique. The performance of the level sets method was further investigated by analysing empirical fMRI data from two subjects performing a visual and a motor task. Our results indicate that the proposed technique provides brain activation results comparable to those obtained by a standard univariate approach, with the advantage that it does not require the definition of a significance threshold.