A Volume Clearing Algorithm for Muon Tomography

TL;DR

This paper introduces MTclear, a novel volume clearing algorithm for muon tomography that improves threat detection by analyzing muon track data to classify regions within a volume, enhancing decision-making capabilities.

Contribution

The paper presents a new algorithm (MTclear) that ray-traces muon tracks and classifies voxels based on track counts and scattering points, improving threat detection in muon tomography.

Findings

Preliminary results demonstrate effective threat classification.

MTclear provides more comprehensive information than conventional methods.

Algorithm works with data from gas electron multiplier-based muon stations.

Abstract

The primary objective is to enhance muon-tomographic image reconstruction capability by providing distinctive information in terms of deciding on the properties of regions or voxels within a probed volume "V" during any point of scanning: threat type, non-threat type, or not-sufficient data. An algorithm (MTclear) is being developed to ray-trace muon tracks and count how many straight tracks are passing through a voxel. If a voxel "v" has sufficient number of straight tracks (t), then "v" is a non-threat type voxel, unless there are sufficient number of scattering points (p) in "v" that will make it a threat-type voxel. The algorithm also keeps track of voxels for which not enough information is known: where p and v both fall below their respective threshold parameters. We present preliminary results showing how the algorithm works on data collected with a Muon Tomography station based on gas electron multipliers operated by our group. The MTclear algorithm provides more comprehensive information to a human operator or to a decision algorithm than that provided by conventional muon-tomographic reconstruction algorithms, in terms of qualitatively determining the threat possibility from a probed volume. This is quite important because only low numbers of cosmic ray source muons are typically available in nature for tomography, while a quick determination of threats is essential.