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. Author manuscript; available in PMC: 2009 Aug 27.
Published in final edited form as: Neuroimage. 2008 Nov 8;45(1 Suppl):S3–15. doi: 10.1016/j.neuroimage.2008.10.043

Fig. 2.

Fig. 2

An overview of the auto context model. Here, H() is a cascade of AdaBoosts. Essentially, the labeling at each iteration of AdaBoost is fed back into the learning process as a new feature along with neighborhood-based information calculated on this map, which allows neighboring voxels to influence each other probabilistically. Convergence criteria and more details are presented in our previous work (Morra et al., 2008c).