In this paper a novel technique to segment tumor voxels in dynamic positron emission tomography (PET) scans is proposed. An inno- vative anomaly detection tool tailored for 3-points dynamic PET scans is designed. The algorithm allows the identification of tumoral cells in dynamic FDG-PET scans thanks to their peculiar anaerobic metabolism experienced over time. The proposed tool is prelimi- narily tested on a small dataset showing promising performance as compared to the state of the art in terms of both accuracy and classi- fication errors.
Automatic method for tumor segmentation from 3-points dynamic PET acquisitions
VERDOJA, FRANCESCO;GRANGETTO, Marco;
2014-01-01
Abstract
In this paper a novel technique to segment tumor voxels in dynamic positron emission tomography (PET) scans is proposed. An inno- vative anomaly detection tool tailored for 3-points dynamic PET scans is designed. The algorithm allows the identification of tumoral cells in dynamic FDG-PET scans thanks to their peculiar anaerobic metabolism experienced over time. The proposed tool is prelimi- narily tested on a small dataset showing promising performance as compared to the state of the art in terms of both accuracy and classi- fication errors.
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