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The analysis of images acquired with Positron Emission Tomography (PET) is challenging. In particular, there is no consensus on the best criterion to quantify the metabolic activity for lesion detection and segmentation purposes. Based on this consideration, we propose a versatile knowledge-based segmentation methodology for 3D PET imaging. In contrast to previous methods, an arbitrary number of quantitative criteria can be involved and the experts behaviour learned and reproduced in order todoi:10.1109/ipta.2015.7367162 dblp:conf/ipta/PadillaGRNKTNGP15 fatcat:ezvp7jvy6ncsth4uhhwxuts3qq