相关论文: A Bayesian Inverse Approach to Proton Therapy Dose…

We propose the BayesDose-Framework, a Bayesian approach for fast and accurate dose prediction in proton therapy. Our framework is based on a previously published deterministic LSTM model and is trained and evaluated on simulated beamlet…

Heavy-ion therapy, particularly using scanned (active) beam delivery, provides a precise and highly conformal dose distribution, with maximum dose deposition for each pencil beam at its endpoint (Bragg peak), and low entrance and exit dose.…

Charged Particle Therapy is a technique for cancer treatment that exploits hadron beams, mostly protons and carbons. A critical issue is the monitoring of the dose released by the beam to the tumor and to the surrounding tissues. We present…

This paper focuses on some dosimetry aspects of proton therapy and pencil beam scanning based on the experience accumulated at Paul Scherrer Institute(PSI). The basic formalism for absolute dosimetry in proton therapy is outlined and the…

In this paper, we use the Bayesian inversion approach to study the data assimilation problem for a family of tumor growth models described by porous-medium type equations. The models contain uncertain parameters and are indexed by a…

Given the sensitivity of proton therapy to anatomical variations, this cancer treatment modality is expected to benefit greatly from integration with magnetic resonance (MR) imaging. One of the obstacles hindering such an integration are…

Inverse problems are of great importance in astrophysics for deriving information about the physical characteristics of hot optically thin plasma sources from their EUV and X-ray spectra. We describe and test an iterative method developed…

Characterizing statistical properties of solutions of inverse problems is essential for decision making. Bayesian inversion offers a tractable framework for this purpose, but current approaches are computationally unfeasible for most…

This paper extends the work of Clarke [1] on the Bayesian foundations of the biomagnetic inverse problem. It derives expressions for the expectation and variance of the a posteriori source current probability distribution given a prior…

Proton beam therapy has been developed to irradiate the tumor with higher precision and dose conformity compared to conventional X-ray irradiation. The dose conformity of this treatment modality may be further improved if narrower proton…

We present a practical method to measure the energy of proton beams at a medical cyclotron using the stacked foil technique in combination with a Bayesian inference method. By measuring the $^{48}$V activity induced in a stack of irradiated…

We present a novel Bayesian framework for inverse problems in which the pos terior distribution is interpreted as the intensity measure of a Poisson point process (PPP). The posterior density is approximated using kernel density estimation,…

A multilayer gaseous detector has been developed for the fast dose-verification measurements of raster-scan-mode therapeutic beams in particle therapy.

Photons are exponentially attenuated in matter producing high doses close to the surface. Therefore they are not well suited for the treatment of deep seated tumours. Charged particles, in contrast, exhibit a sharp increase of ionisation…

This study presents a Bayesian framework for (inverse) uncertainty quantification and parameter estimation in a two-step Chemical Vapor Deposition coating process using production data. We develop an XGBoost surrogate model that maps…

Energy resolved neutron transmission techniques can provide high-resolution images of strain within polycrystalline samples allowing the study of residual strain and stress in engineered components. Strain is estimated from such data by…

In this work, we present a fundamental mathematical model for proton transport, tailored to capture the key physical processes underpinning Proton Beam Therapy (PBT). The model provides a robust and computationally efficient framework for…

A common task in experimental sciences is to fit mathematical models to real-world measurements to improve understanding of natural phenomenon (reverse-engineering or inverse modeling). When complex dynamical systems are considered, such as…

Proton beam radiotherapy stands at the forefront of precision cancer treatment, leveraging the unique physical interactions of proton beams with human tissue to deliver minimal dose upon entry and deposit the therapeutic dose precisely at…

We propose a Bayesian inference framework to estimate uncertainties in inverse scattering problems. Given the observed data, the forward model and their uncertainties, we find the posterior distribution over a finite parameter field…