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

Fuente: arXiv

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Main Authors:	Aehle, M., Alme, J., Barnaföldi, G. G., Bíró, G., Bodova, T., Borshchov, V., Brink, A. van den, Chaar, M., Dudás, B., Eikeland, V., Feofilov, G., Garth, C., Gauger, N. R., Grøttvik, O., Helstrup, H., Igolkin, S., Jólesz, Zs., Keidel, R., Kobdaj, C., Kortus, T., Kusch, L., Leonhardt, V., Mehendale, S., Ningappa, R., Odland, O. H., O'Neill, G., Papp, G., Peitzmann, T., Pettersen, H. E. S., Piersimoni, P., Protsenko, M., Rauch, M., Rehman, A. Ur, Richter, M., Röhrich, D., Santana, J., Schilling, A., Seco, J., Songmoolnak, A., Sølie, J. Rambo, Tambave, G., Tymchuk, I., Ullaland, K., Varga-Kőfaragó, M., Volz, L., Wagner, B., Wendzel, S., Wiebel, A., Xiao, R., Yang, S., Yokoyama, H., Zillien, S.
Format:	Preprint
Published:	2025
Subjects:	Computational Physics Instrumentation and Detectors Medical Physics
Online Access:	Acceder al recurso
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_version_	1866916054098247680
author	Aehle, M. Alme, J. Barnaföldi, G. G. Bíró, G. Bodova, T. Borshchov, V. Brink, A. van den Chaar, M. Dudás, B. Eikeland, V. Feofilov, G. Garth, C. Gauger, N. R. Grøttvik, O. Helstrup, H. Igolkin, S. Jólesz, Zs. Keidel, R. Kobdaj, C. Kortus, T. Kusch, L. Leonhardt, V. Mehendale, S. Ningappa, R. Odland, O. H. O'Neill, G. Papp, G. Peitzmann, T. Pettersen, H. E. S. Piersimoni, P. Protsenko, M. Rauch, M. Rehman, A. Ur Richter, M. Röhrich, D. Santana, J. Schilling, A. Seco, J. Songmoolnak, A. Sølie, J. Rambo Tambave, G. Tymchuk, I. Ullaland, K. Varga-Kőfaragó, M. Volz, L. Wagner, B. Wendzel, S. Wiebel, A. Xiao, R. Yang, S. Yokoyama, H. Zillien, S.
author_facet	Aehle, M. Alme, J. Barnaföldi, G. G. Bíró, G. Bodova, T. Borshchov, V. Brink, A. van den Chaar, M. Dudás, B. Eikeland, V. Feofilov, G. Garth, C. Gauger, N. R. Grøttvik, O. Helstrup, H. Igolkin, S. Jólesz, Zs. Keidel, R. Kobdaj, C. Kortus, T. Kusch, L. Leonhardt, V. Mehendale, S. Ningappa, R. Odland, O. H. O'Neill, G. Papp, G. Peitzmann, T. Pettersen, H. E. S. Piersimoni, P. Protsenko, M. Rauch, M. Rehman, A. Ur Richter, M. Röhrich, D. Santana, J. Schilling, A. Seco, J. Songmoolnak, A. Sølie, J. Rambo Tambave, G. Tymchuk, I. Ullaland, K. Varga-Kőfaragó, M. Volz, L. Wagner, B. Wendzel, S. Wiebel, A. Xiao, R. Yang, S. Yokoyama, H. Zillien, S.
contents	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.
format	Preprint
id	arxiv_https___arxiv_org_abs_2503_02788
institution	arXiv
publishDate	2025
record_format	arxiv
spellingShingle	Reconstruction of proton relative stopping power with a granular calorimeter detector model Aehle, M. Alme, J. Barnaföldi, G. G. Bíró, G. Bodova, T. Borshchov, V. Brink, A. van den Chaar, M. Dudás, B. Eikeland, V. Feofilov, G. Garth, C. Gauger, N. R. Grøttvik, O. Helstrup, H. Igolkin, S. Jólesz, Zs. Keidel, R. Kobdaj, C. Kortus, T. Kusch, L. Leonhardt, V. Mehendale, S. Ningappa, R. Odland, O. H. O'Neill, G. Papp, G. Peitzmann, T. Pettersen, H. E. S. Piersimoni, P. Protsenko, M. Rauch, M. Rehman, A. Ur Richter, M. Röhrich, D. Santana, J. Schilling, A. Seco, J. Songmoolnak, A. Sølie, J. Rambo Tambave, G. Tymchuk, I. Ullaland, K. Varga-Kőfaragó, M. Volz, L. Wagner, B. Wendzel, S. Wiebel, A. Xiao, R. Yang, S. Yokoyama, H. Zillien, S. Computational Physics Instrumentation and Detectors Medical Physics 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.
title	Reconstruction of proton relative stopping power with a granular calorimeter detector model
topic	Computational Physics Instrumentation and Detectors Medical Physics
url	https://arxiv.org/abs/2503.02788