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Computed tomography (CT) is the imaging modality used to calculate the deposit of dose in radiotherapy planning, where the physical interactions are modelled based upon the electron density, which can be calculated from CT images. Traditionally this is a three step process: linearising the raw x-ray measurements and correcting for beam-hardening and scatter; inverting the system with analytic or iterative reconstruction algorithms into linear attenuation coefficient; then applying a nonlinear calibration into electron density. In this work, we propose a new method for statistically inferring a quantitative image of electron density directly from the raw CT measurements, with no pre- or post-processing necessary, and able to cope with both beam-hardening from a single polyenergetic source and additive scatter. We evaluate this concept with cone-beam CT (CBCT) imaging for bladder cancer, where we demonstrate significantly higher electron density accuracy than other quantitative approaches. We also show through simulated photon and proton beam calculation, that our method may facilitate superior dose estimation, especially with regions containing bony structures.
|Title of host publication||Medical Image Understanding and Analysis - 21st Annual Conference, MIUA 2017, Proceedings|
|Number of pages||12|
|Publication status||Published - 2017|
|Event||21st Annual Conference on Medical Image Understanding and Analysis, MIUA 2017 - Edinburgh, United Kingdom|
Duration: 11 Jul 2017 → 13 Jul 2017
|Name||Communications in Computer and Information Science|
|Conference||21st Annual Conference on Medical Image Understanding and Analysis, MIUA 2017|
|Period||11/07/17 → 13/07/17|
- Computed tomography
- Proton therapy
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