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Reconstruction of proton relative stopping power with a granular calorimeter detector model

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arxiv 2503.02788 v1 pith:I2JGFRPQ submitted 2025-03-04 physics.comp-ph physics.ins-detphysics.med-ph

Reconstruction of proton relative stopping power with a granular calorimeter detector model

classification physics.comp-ph physics.ins-detphysics.med-ph
keywords reconstructionhadrontherapyaimsalgorithmsdosemethodplanning
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Proton computed tomography (pCT) aims to facilitate precise dose planning for hadron therapy, a promising and effective method for cancer treatment. Hadron therapy utilizes protons and heavy ions to deliver well focused doses of radiation, leveraging the Bragg peak phenomenon to target tumors while sparing healthy tissues. The Bergen pCT Collaboration aims to develop a novel pCT scanner, and accompanying reconstruction algorithms to overcome current limitations. This paper focuses on advancing the track- and image reconstruction algorithms, thereby enhancing the precision of the dose planning and reducing side effects of hadron therapy. A neural network aided track reconstruction method is presented.

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