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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Joint Segmentation and CT Synthesis for MRI-only Radiotherapy Treatment Planning
verfasst von : Ninon Burgos, Filipa Guerreiro, Jamie McClelland, Simeon Nill, David Dearnaley, Nandita deSouza, Uwe Oelfke, Antje-Christin Knopf, Sébastien Ourselin, M. Jorge Cardoso
Erschienen in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016
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Abstract
Accurate knowledge of organ location and tissue attenuation properties are the two essential components to perform radiotherapy treatment planning (RTP). Computed tomography (CT) has been the modality of choice for RTP as it easily provides electron density information. However, its low soft tissue contrast limits the accuracy of organ delineation. On the contrary, magnetic resonance (MR) provides images with excellent soft tissue contrast but its use for RTP is limited by the fact that it does not readily provide tissue attenuation information.
In this work we propose a multi-atlas information propagation scheme that jointly segments the organs at risk and generates pseudo CT data from MR images. We demonstrate that the proposed framework is able to automatically generate accurate pseudo CT images and segmentations in the pelvic region, bypassing the need for CT scan for accurate RTP.