We extend MIST by introducing a more flexible MRF-based shape model.
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We segment the substantia nigra, subthalamic nucleus and red nucleus in 7 T data.
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The method produces high-quality results in different age groups.
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We investigate how image intensity influences manual and automatic segmentation.
Abstract
With recent developments in MR acquisition at 7 T, smaller brainstem structures such as the red nuclei, substantia nigra and subthalamic nuclei can be imaged with good contrast and resolution. These structures have important roles both in the study of the healthy brain and in diseases such as Parkinson's disease, but few methods have been described to automatically segment them. In this paper, we extend a method that we have previously proposed for segmentation of the striatum and globus pallidus to segment these deeper and smaller structures. We modify the method to allow more direct control over segmentation smoothness by using a Markov random field prior. We investigate segmentation performance in three age groups and show that the method produces consistent results that correspond well with manual segmentations. We perform a vertex-based analysis to identify changes with age in the shape of the structures and present results suggesting that the method may be at least as effective as manual delineation in capturing differences between subjects.
