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Matthew Toews, William M Wells, and Lilla Zöllei. 2012. “A Feature-based Developmental Model of the Infant Brain in Structural MRI”. Med Image Comput Comput Assist Interv, 15, Pt 2, Pp. 204-11.
In this paper, anatomical development is modeled as a collection of distinctive image patterns localized in space and time. A Bayesian posterior probability is defined over a random variable of subject age, conditioned on data in the form of scale-invariant image features. The model is automatically learned from a large set of images exhibiting significant variation, used to discover anatomical structure related to age and development, and fit to new images to predict age. The model is applied to a set of 230 infant structural MRIs of 92 subjects acquired at multiple sites over an age range of 8-590 days. Experiments demonstrate that the model can be used to identify age-related anatomical structure, and to predict the age of new subjects with an average error of 72 days.Last updated on 02/24/2023