Exploration of differentiability in a proton computed tomography simulation framework.

Gradient-based optimization using algorithmic derivatives can be a useful technique to improve engineering designs with respect to a computer-implemented objective function. Likewise, uncertainty quantification through computer simulations can be carried out by means of derivatives of the computer simulation. However, the effectiveness of these techniques depends on how 'well-linearizable' the software is.

Uncertainty-aware spot rejection rate as quality metric for proton therapy using a digital tracking calorimeter.

Proton therapy is highly sensitive to range uncertainties due to the nature of the dose deposition of charged particles. To ensure treatment quality, range verification methods can be used to verify that the individual spots in a pencil beam scanning treatment fraction match the treatment plan. This study introduces a novel metric for proton therapy quality control based on uncertainties in range verification of individual spots.

Visual Cue Based Corrective Feedback for Motor Skill Training in Mixed Reality: A Survey.

When learning a motor skill it is helpful to get corrective feedback from an instructor. This will support the learner to execute the movement correctly. With modern technology, it is possible to provide this feedback via mixed reality.

Investigating particle track topology for range telescopes in particle radiography using convolutional neural networks.

Background: Proton computed tomography (pCT) and radiography (pRad) are proposed modalities for improved treatment plan accuracy and treatment validation in proton therapy. The pCT system of the Bergen pCT collaboration is able to handle very high particle intensities by means of track reconstruction. However, incorrectly reconstructed and secondary tracks degrade the image quality.

A Model of Spatial Directness in Interactive Visualization.

We discuss the concept of directness in the context of spatial interaction with visualization. In particular, we propose a model that allows practitioners to analyze and describe the spatial directness of interaction techniques, ultimately to be able to better understand interaction issues that may affect usability. To reach these goals, we distinguish between different types of directness.