Reconstruction of proton relative stopping power with a granular calorimeter detector model
Computational Physics
2026-05-28 v1 Instrumentation and Detectors
Medical Physics
Abstract
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.
Keywords
Cite
@article{arxiv.2503.02788,
title = {Reconstruction of proton relative stopping power with a granular calorimeter detector model},
author = {M. Aehle and J. Alme and G. G. Barnaföldi and G. Bíró and T. Bodova and V. Borshchov and A. van den Brink and M. Chaar and B. Dudás and V. Eikeland and G. Feofilov and C. Garth and N. R. Gauger and O. Grøttvik and H. Helstrup and S. Igolkin and Zs. Jólesz and R. Keidel and C. Kobdaj and T. Kortus and L. Kusch and V. Leonhardt and S. Mehendale and R. Ningappa and O. H. Odland and G. O'Neill and G. Papp and T. Peitzmann and H. E. S. Pettersen and P. Piersimoni and M. Protsenko and M. Rauch and A. Ur Rehman and M. Richter and D. Röhrich and J. Santana and A. Schilling and J. Seco and A. Songmoolnak and J. Rambo Sølie and G. Tambave and I. Tymchuk and K. Ullaland and M. Varga-Kőfaragó and L. Volz and B. Wagner and S. Wendzel and A. Wiebel and R. Xiao and S. Yang and H. Yokoyama and S. Zillien},
journal= {arXiv preprint arXiv:2503.02788},
year = {2026}
}
Comments
14 pages, 6 figures, 1 table