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136. Böhlen, T.T., Cerutti, F., Dosanjh, M. et al.: Benchmarking nuclear models of FLUKA and
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137. Dedes, G., Pinto, M., Dauvergne, D. et al.: Assessment and improvements of Geant4 hadronic
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120. Adloff, C., Blaha, J., Blaising, J.-J. et al.: Validation of GEANT4 Monte Carlo models with
a highly granular scintillator-steel hadron calorimeter. J. Instrum. 8, P07005 (2013). https://
doi.org/10.1088/1748-0221/8/07/P07005
121. Santina, G., Nieminen, P., Evansa, H. et al.: New Geant4 based simulation tools for space
radiation shielding and effects analysis. Nucl. Phys. B - Proc. Suppl. 125, 69–74 (2003).
https://doi.org/10.1016/S0920-5632(03)90968-6
122. Santin, G., Ivanchenko, V., Evans, H. et al.: GRAS: a general-purpose 3-D Modular
Simulation tool for space environment effects analysis. IEEE Trans. Nucl. Sci. 52, 2294–2299
(2005). https://doi.org/10.1109/TNS.2005.860749
123. Gillam, J.E., Rafecas, M.: Monte-Carlo simulations and image reconstruction for novel
imaging scenarios in emission tomography. Nucl. Instruments Methods Phys. Res. Sect.
A Accel. Spectrometers, Detect. Assoc. Equip. 809, 76–88 (2016). https://doi.org/10.1016/
J.NIMA.2015.09.084
124. Castiglioni, I., Cremonesi, O., Gilardi, M.C. et al.: Scatter correction techniques in 3D PET:
a Monte Carlo evaluation. IEEE Trans. Nucl. Sci. 46, 2053–2058 (1999). https://doi.org/
10.1109/23.819282
125. Strulab, D., Santin, G., Lazaro, D. et al.: GATE (geant4 application for tomographic
emission): a PET/SPECT general-purpose simulation platform. Nucl. Phys. B - Proc. Suppl.
125, 75–79 (2003). https://doi.org/10.1016/S0920-5632(03)90969-8
126. Arce, P., Lagares, J.I., Harkness, L. et al.: GAMOS: An easy and flexible way to use
GEANT4. In: 2011 IEEE Nuclear Science Symposium Conference Record. pp. 2230–2237.
IEEE (2011)
127. España, S., Herraiz, J.L., Vicente, E. et al.: PeneloPET, a Monte Carlo PET simulation tool
based on PENELOPE: features and validation. Phys. Med. Biol. 54, 1723–1742 (2009). https:/
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128. Barret, O., Carpenter, T.A., Clark, J.C. et al.: Monte Carlo simulation and scatter correction
of the GE Advance PET scanner with SimSET and Geant4. Phys. Med. Biol. 50, 4823–4840
(2005). https://doi.org/10.1088/0031-9155/50/20/006
129. Kawrakow, I., Mitev, K., Gerganov, G. et al.: SU-GG-I-109: Using EGSnrc Within GATE
to Improve the Efficiency Of positron Emission Tomography Simulations. Med. Phys. 35,
2667–2667 (2008). https://doi.org/10.1118/1.2961507
130. Seco, J.: Monte carlo techniques in radiation therapy. CRC Press (2016)
131. Zacharatou Jarlskog, C., Paganetti, H.: Physics Settings for Using the Geant4 Toolkit in
Proton Therapy. IEEE Trans. Nucl. Sci. 55, 1018–1025 (2008). https://doi.org/10.1109/
TNS.2008.922816
132. Paganetti, H., Jiang, H., Parodi, K. et al.: Clinical implementation of full Monte Carlo dose
calculation in proton beam therapy. Phys. Med. Biol. 53, 4825–4853 (2008). https://doi.org/
10.1088/0031-9155/53/17/023
133. Paganetti, H., Jiang, H., Adams, J.A. et al.: Monte Carlo simulations with time-dependent
geometries to investigate effects of organ motion with high temporal resolution. Int. J. Radiat.
Oncol. Biol. Phys. 60, 942–50 (2004). https://doi.org/10.1016/j.ijrobp.2004.06.024
134. Aso, T., Yamashita, T., Akagi, T. et al.: Validation of PTSIM for clinical usage. In: IEEE
Nuclear Science Symposuim & Medical Imaging Conference. pp. 158–160. IEEE (2010)
135. Perl, J., Shin, J., Schümann, J. et al.: TOPAS: An innovative proton Monte Carlo platform for
research and clinical applications. Med. Phys. 39, 6818–6837 (2012). https://doi.org/10.1118/
1.4758060
136. Böhlen, T.T., Cerutti, F., Dosanjh, M. et al.: Benchmarking nuclear models of FLUKA and
GEANT4 for carbon ion therapy. Phys. Med. Biol. 55, 5833–5847 (2010). https://doi.org/
10.1088/0031-9155/55/19/014
137. Dedes, G., Pinto, M., Dauvergne, D. et al.: Assessment and improvements of Geant4 hadronic
models in the context of prompt-gamma hadrontherapy monitoring. Phys. Med. Biol. 59,
1747–1772 (2014). https://doi.org/10.1088/0031-9155/59/7/1747