Multicriteria 3D PET image segmentation

Francisco Javier Alvarez Padilla, Eloise Grossiord, Barbara Romaniuk, Benoit Naegel, Camille Kurtz, Hugues Talbot, Laurent Najman, Romain Guillemot, Dimitri Papathanassiou, Nicolas Passat
2015 2015 International Conference on Image Processing Theory, Tools and Applications (IPTA)  
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 to
more » ... ide the segmentation process. The classification part of the scheme relies on example-based learning strategies, allowing interactive example definition and more generally incremental refinement. The image processing part relies on hierarchical segmentation, allowing vectorial attribute handling. Preliminary results on synthetic and real images confirm the relevance of this methodology, both as a segmentation approach and as an experimental framework for criteria evaluation.
doi:10.1109/ipta.2015.7367162 dblp:conf/ipta/PadillaGRNKTNGP15 fatcat:ezvp7jvy6ncsth4uhhwxuts3qq