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@ARTICLE{Schilling:299787,
      author       = {A. Schilling and M. Aehle and J. Alme and G. G. Barnaföldi
                      and G. Bíró and T. Bodova and V. Borshchov and A. van den
                      Brink and V. N. Eikeland and G. Feofilov and C. Garth and N.
                      R. Gauger and O. S. Grøttvik and H. Helstrup and S. Igolkin
                      and J. G. Johansen and R. Keidel and C. Kobdaj and T. Kortus
                      and V. Leonhardt and S. Mehendale and R. N. Mulawade 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. U. Rehman and M. Richter and D. Röhrich and J.
                      Santana and J. Seco$^*$ and A. Songmoolnak and Á. Sudár
                      and G. Tambave and I. Tymchuk and K. Ullaland and M.
                      Varga-Kőfaragó and B. Wagner and R. Xiao and S. Yang},
      title        = {{M}odeling {C}harge {C}ollection in {S}ilicon {P}ixel
                      {D}etectors for {P}roton {T}herapy {A}pplications.},
      journal      = {Biomedical physics $\&$ engineering express},
      volume       = {11},
      number       = {3},
      issn         = {2057-1976},
      address      = {Bristol},
      publisher    = {IOP Publ.},
      reportid     = {DKFZ-2025-00542},
      pages        = {035005},
      year         = {2025},
      note         = {Biomed. Phys. Eng. Express 11 (2025) 035005},
      abstract     = {Objective.Monolithic active pixel sensors are used for
                      charged particle tracking in many applications, from medical
                      physics to astrophysics. The Bergen pCT collaboration
                      designed a sampling calorimeter for proton computed
                      tomography, based entirely on the ALICE PIxel DEtector
                      (ALPIDE). The same telescope can be used for in-situ range
                      verification in particle therapy. An accurate charge
                      diffusion model is required to convert the deposited energy
                      from Monte Carlo simulations to a cluster of pixels, and to
                      estimate the deposited energy, given an experimentally
                      observed cluster.Approach.We optimize the parameters of
                      different charge diffusion models to experimental data for
                      both proton computed tomography and proton range
                      verification, collected at the Danish Centre for Particle
                      Therapy. We then evaluate the performance of downstream
                      tasks to investigate the impact of charge diffusion
                      modeling.Main results.We find that it is beneficial to
                      optimize application-specific models, with a power law
                      working best for proton computed tomography, and a model
                      based on a 2D Cauchy-Lorentz distribution giving better
                      agreement for range verification. We further highlight the
                      importance of evaluating the downstream tasks with multiple
                      approaches to obtain a range of expected performance metrics
                      for the application.Significance.This work demonstrates the
                      influence of the charge diffusion model on downstream tasks,
                      and recommends a new model for proton range verification
                      with an ALPIDE-based pixel telescope.},
      keywords     = {charge diffusion (Other) / monolithic active pixel sensor
                      (Other) / proton computed tomography (Other) / proton
                      therapy (Other) / range verification (Other)},
      cin          = {E041},
      ddc          = {610},
      cid          = {I:(DE-He78)E041-20160331},
      pnm          = {315 - Bildgebung und Radioonkologie (POF4-315)},
      pid          = {G:(DE-HGF)POF4-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40073455},
      doi          = {10.1088/2057-1976/adbf9c},
      url          = {https://inrepo02.dkfz.de/record/299787},
}