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

M. Aehle; J. Alme; G.G. Barnaföldi; G. Bíró; T. Bodova; V. Borshchov; A. van den Brink; M. Chaar; B. Dudás; V. Eikeland; G. Feofilov; C. Garth; N.R. Gauger; O. Grøttvik; H. Helstrup; S. Igolkin; Z. Jólesz; R. Keidel; C. Kobdaj; T. Kortus; L. Kusch; V. Leonhardt; S. Mehendale; R. Ningappa Mulawade; O.H. Odland; G. O'Neill; G. Papp; T. Peitzmann; H.E.S. Pettersen; P. Piersimoni; M.P. Protsenko; M. Rauch; A. Ur Rehman; M. Richter; D. Röhrich; J. Santana; A. Schilling; J. Seco; A. Songmoolnak; J. Rambo Sølie; G. Tambave; I. Tymchuk; K. Ullaland; M. Varga-Kőfaragó; L. Volz; B. Wagner; S. Wendzel; A. Wiebel; R. Xiao; S. Yang; H. Yokoyama; S. Zillien

doi:10.1142/S0217751X25420084

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

M. Aehle
, J. Alme
, G.G. Barnaföldi
, G. Bíró (Corresponding author)
, T. Bodova
, V. Borshchov
, A. van den Brink
, M. Chaar
, B. Dudás
, V. Eikeland
, G. Feofilov
, C. Garth
, N.R. Gauger
, O. Grøttvik
, H. Helstrup
, S. Igolkin
, Z. Jólesz
, R. Keidel
, C. Kobdaj
, T. Kortus

L. Kusch, V. Leonhardt, S. Mehendale, R. Ningappa Mulawade, O.H. Odland, G. O'Neill, G. Papp, T. Peitzmann, H.E.S. Pettersen, P. Piersimoni, M.P. Protsenko, M. Rauch, A. Ur Rehman, M. Richter, D. Röhrich, J. Santana, A. Schilling, J. Seco, A. Songmoolnak, J. Rambo Sølie, G. Tambave, I. Tymchuk, K. Ullaland, M. Varga-Kőfaragó, L. Volz, B. Wagner, S. Wendzel, A. Wiebel, R. Xiao, S. Yang, H. Yokoyama, S. Zillien

Computational Illumination Optics

Research output: Contribution to journal › Article › Academic › peer-review

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.

Original language	English
Article number	2542008
Journal	International Journal of Modern Physics A
Volume	40
Issue number	21
DOIs	https://doi.org/10.1142/S0217751X25420084
Publication status	Published - 30 Jul 2025

Funding

This work has been supported by the NKFIH grants OTKA K135515 and the 2024- 1.2.5-TET-2024-00022, 2021-4.1.2-NEMZ KI-2024-00031 and 2021-4.1.2-NEMZ KI- 2024-00033 projects.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Hadron therapy
image reconstruction
machine learning
proton computed tomography

Access to Document

10.1142/S0217751X25420084

Cite this

Aehle, M., Alme, J., Barnaföldi, G. G., Bíró, G., Bodova, T., Borshchov, V., van den Brink, A., Chaar, M., Dudás, B., Eikeland, V., Feofilov, G., Garth, C., Gauger, N. R., Grøttvik, O., Helstrup, H., Igolkin, S., Jólesz, Z., Keidel, R., Kobdaj, C., ... Zillien, S. (2025). Reconstruction of proton relative stopping power with a granular calorimeter detector model. International Journal of Modern Physics A, 40(21), Article 2542008. https://doi.org/10.1142/S0217751X25420084

@article{d19cf761475748149a0ef340ca2ce517,

title = "Reconstruction of proton relative stopping power with a granular calorimeter detector model",

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 = "Hadron therapy, image reconstruction, machine learning, proton computed tomography",

author = "M. Aehle and J. Alme and G.G. Barnaf{\"o}ldi and G. B{\'i}r{\'o} and T. Bodova and V. Borshchov and \{van den Brink\}, A. and M. Chaar and B. Dud{\'a}s and V. Eikeland and G. Feofilov and C. Garth and N.R. Gauger and O. Gr{\o}ttvik and H. Helstrup and S. Igolkin and Z. J{\'o}lesz and R. Keidel and C. Kobdaj and T. Kortus and L. Kusch and V. Leonhardt and S. Mehendale and \{Ningappa Mulawade\}, R. and O.H. Odland and G. O'Neill and G. Papp and T. Peitzmann and H.E.S. Pettersen and P. Piersimoni and M.P. Protsenko and M. Rauch and \{Ur Rehman\}, A. and M. Richter and D. R{\"o}hrich and J. Santana and A. Schilling and J. Seco and A. Songmoolnak and \{Rambo S{\o}lie\}, J. and G. Tambave and I. Tymchuk and K. Ullaland and M. Varga-K{\H o}farag{\'o} and L. Volz and B. Wagner and S. Wendzel and A. Wiebel and R. Xiao and S. Yang and H. Yokoyama and S. Zillien",

year = "2025",

month = jul,

day = "30",

doi = "10.1142/S0217751X25420084",

language = "English",

volume = "40",

journal = "International Journal of Modern Physics A",

issn = "0217-751X",

publisher = "World Scientific",

number = "21",

}

Aehle, M, Alme, J, Barnaföldi, GG, Bíró, G, Bodova, T, Borshchov, V, van den Brink, A, Chaar, M, Dudás, B, Eikeland, V, Feofilov, G, Garth, C, Gauger, NR, Grøttvik, O, Helstrup, H, Igolkin, S, Jólesz, Z, Keidel, R, Kobdaj, C, Kortus, T, Kusch, L, Leonhardt, V, Mehendale, S, Ningappa Mulawade, R, Odland, OH, O'Neill, G, Papp, G, Peitzmann, T, Pettersen, HES, Piersimoni, P, Protsenko, MP, Rauch, M, Ur Rehman, A, Richter, M, Röhrich, D, Santana, J, Schilling, A, Seco, J, Songmoolnak, A, Rambo Sølie, J, 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 2025, 'Reconstruction of proton relative stopping power with a granular calorimeter detector model', International Journal of Modern Physics A, vol. 40, no. 21, 2542008. https://doi.org/10.1142/S0217751X25420084

TY - JOUR

T1 - Reconstruction of proton relative stopping power with a granular calorimeter detector model

AU - Aehle, M.

AU - Alme, J.

AU - Barnaföldi, G.G.

AU - Bíró, G.

AU - Bodova, T.

AU - Borshchov, V.

AU - van den Brink, A.

AU - Chaar, M.

AU - Dudás, B.

AU - Eikeland, V.

AU - Feofilov, G.

AU - Garth, C.

AU - Gauger, N.R.

AU - Grøttvik, O.

AU - Helstrup, H.

AU - Igolkin, S.

AU - Jólesz, Z.

AU - Keidel, R.

AU - Kobdaj, C.

AU - Kortus, T.

AU - Kusch, L.

AU - Leonhardt, V.

AU - Mehendale, S.

AU - Ningappa Mulawade, R.

AU - Odland, O.H.

AU - O'Neill, G.

AU - Papp, G.

AU - Peitzmann, T.

AU - Pettersen, H.E.S.

AU - Piersimoni, P.

AU - Protsenko, M.P.

AU - Rauch, M.

AU - Ur Rehman, A.

AU - Richter, M.

AU - Röhrich, D.

AU - Santana, J.

AU - Schilling, A.

AU - Seco, J.

AU - Songmoolnak, A.

AU - Rambo Sølie, J.

AU - Tambave, G.

AU - Tymchuk, I.

AU - Ullaland, K.

AU - Varga-Kőfaragó, M.

AU - Volz, L.

AU - Wagner, B.

AU - Wendzel, S.

AU - Wiebel, A.

AU - Xiao, R.

AU - Yang, S.

AU - Yokoyama, H.

AU - Zillien, S.

PY - 2025/7/30

Y1 - 2025/7/30

N2 - 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.

AB - 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.

KW - Hadron therapy

KW - image reconstruction

KW - machine learning

KW - proton computed tomography

UR - https://www.scopus.com/pages/publications/105003742457

U2 - 10.1142/S0217751X25420084

DO - 10.1142/S0217751X25420084

M3 - Article

AN - SCOPUS:105003742457

SN - 0217-751X

VL - 40

JO - International Journal of Modern Physics A

JF - International Journal of Modern Physics A

IS - 21

M1 - 2542008

ER -

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

Abstract

Funding

UN SDGs

Keywords

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