Abstract
We present a quantitative evaluation of MR brain images segmentation. Five classifiers were tested. The task was to classify an MR image into four different classes: background, cortical spinal fluid, gray matter and white matter. The performance was rated by first estimating a ground truth (EGT) using STAPLE and then analyzing the volume differences as well as the Dice similarity measure between each of the 5 classifiers. © Springer-Verlag Berlin Heidelberg 2004.
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CITATION STYLE
Bouix, S., Ungar, L., Dickey, C. C., McCarley, R. W., & Shenton, M. E. (2004). Evaluating automatic brain tissue classifiers. In Lecture Notes in Computer Science (Vol. 3217, pp. 1038–1039). Springer Verlag. https://doi.org/10.1007/978-3-540-30136-3_127
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