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Accurate and reliable measurement of pulmonary nodule size from CT scans has an important role in computer assisted evaluation of lung lesions. It is a key factor in the diagnosis of lung cancer as the estimation of nodule growth rates serves as a predictor of malignancy; size change can also be used to assess the efficacy of a therapeutic treatment. Additionally, nodule sizing is a critical aspect of computer assisted diagnosis (CAD) systems, and in particular their detection sub-systems, because they are always qualified with respect to a given size range of nodules.

In the context of spatial extent for a three-dimensional object without restrictions on shape, the size is best expressed by the volume occupied by that object. However, other factors, e.g. imaging modality or readers' resource availability, may influence the selection of a method for size estimation. This research project aims at studying the reciprocal relationships between different size estimation methods, investingating both the differences in the actual sizes reported and the effects on readers' variability.