A Review of Mixed-Effect Modeling in the Longitudinal Studies Using Medical Images of Patients
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In this review paper, some applications of the mixed effect modeling in medial image processing and longitudinal analysis is studied. For this purpose, a general structure is extracted from some of the researches in the literature. This structure includes a number of essential elements, each of which having a few design choices, namely 1) tracked features, 2) models mathematical expression and random effects and finally 3) response prediction. Two research study examples in Alzheimers disease and prostate tomography are also briefly introduced to further discuss the above design choices.
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