Related papers: Pre-treatment radiotherapy dose verification using…
Purpose: To describe the dosimetric commissioning and quality assurance (QA) of the actively scanned proton and carbon ion beams at the Italian National Center for Oncological Hadrontherapy. Methods: The laterally integrated…
The distortion of light's degrees of freedom when passing through complex random media is of great interest across a diversity of fields, e.g., scattering in biological studies. Emulating such media in a controlled laboratory setting…
Plastic scintillation detectors are increasingly used to measure dose distributions in the context of radiotherapy treatments. Their water-equivalence, real-time response and high spatial resolution distinguish them from traditional…
Computed tomography (CT) involves a patient's exposure to ionizing radiation. To reduce the radiation dose, we can either lower the X-ray photon count or down-sample projection views. However, either of the ways often compromises image…
Image reconstruction in Single Photon Emission Computed Tomography (SPECT) is affected by physical effects such as photon attenuation, Compton scatter and detector response. These effects can be compensated for by modeling the corresponding…
An algorithm for creating synthetic telescope images of Smoothed Particle Hydrodynamics (SPH) density fields is presented, which utilises the adaptive nature of the SPH formalism in full. The imaging process uses Monte Carlo Radiative…
Spectropolarimetric reconstructions of the photospheric vector magnetic field are intrinsically limited by the so-called 180$^\circ$ ambiguity in the orientation of the transverse component. The successful launch and operation of Solar…
X-ray dose constantly gains interest in the interventional suite. With dose being generally difficult to monitor reliably, fast computational methods are desirable. A major drawback of the gold standard based on Monte Carlo (MC) methods is…
We demonstrate the application of mixture density networks (MDNs) in the context of automated radiation therapy treatment planning. It is shown that an MDN can produce good predictions of dose distributions as well as reflect uncertain…
Purpose: The purpose of this work is to develop a new approach for high spatial resolution dosimetry based on Raman micro-spectroscopy scanning of radiochromic film (RCF). We generate dose calibration curves over an extended dose range from…
Super-Droplet Method (SDM) is a probabilistic Monte-Carlo-type model of particle coagulation process, an alternative to the mean-field formulation of Smoluchowski. SDM as an algorithm has linear computational complexity with respect to the…
Forward uncertainty quantification (UQ) for partial differential equations is a many-query task that requires a significant number of model evaluations. The objective of this work is to mitigate the computational cost of UQ for a 3D-1D…
Purpose: To obtain individualized internal doses with a Monte Carlo method in patients undergoing diagnostic FCH-PET studies and to compare such doses with the MIRD method calculations. Methods: A patient cohort of 17 males were imaged…
Stereotactic body radiation therapy (SBRT) for pancreatic cancer requires a skillful approach to deliver ablative doses to the tumor while limiting dose to the highly sensitive duodenum, stomach, and small bowel. Here, we develop…
FLASH is a new treatment modality that requires optimization of dose, dose rate, and LET. Here we validate these three quantities under FLASH conditions, which includes the quantum uncertainty in the time-dependent instantaneous dose rate…
SPECT imaging is one of the common modalities used to examine kidney disease. The radiopharmaceuticals such as 99mTc-MAG3, 99mTc-DTPA, and 99mTc-DMSA are commonly employed for pediatric patients. It is generally accepted that children…
The Fast Dose Calculator (FDC), a track repeating algorithm Monte Carlo method was initially developed for proton therapy. The validation for proton therapy has been demonstrated in a previous work. This method can be expanded to ion…
This work aims to study the generalizability of a pre-developed deep learning (DL) dose prediction model for volumetric modulated arc therapy (VMAT) for prostate cancer and to adapt the model to three different internal treatment planning…
Magnetic Resonance Imaging (MRI) is used in everyday clinical practice to assess brain tumors. Several automatic or semi-automatic segmentation algorithms have been introduced to segment brain tumors and achieve an expert-like accuracy.…
Particle therapy is an established method to treat deep-seated tumours using accelerator-produced ion beams. For treatment planning, the precise knowledge of the relative stopping power (RSP) within the patient is vital. Conversion errors…