Image characterization metrics for muon tomography

Autor: Matt Steiger, Joel Kindem, Andre Lehovich, Edward Anashkin, Weidong Luo, Chuanyong Bai, Michael James Sossong
Rok vydání: 2014
Předmět:
Zdroj: SPIE Proceedings.
ISSN: 0277-786X
DOI: 10.1117/12.2049972
Popis: Muon tomography uses naturally occurring cosmic rays to detect nuclear threats in containers. Currently there are no systematic image characterization metrics for muon tomography. We propose a set of image characterization methods to quantify the imaging performance of muon tomography. These methods include tests of spatial resolution, uniformity, contrast, signal to noise ratio (SNR) and vertical smearing. Simulated phantom data and analysis methods were developed to evaluate metric applicability. Spatial resolution was determined as the FWHM of the point spread functions in X, Y and Z axis for 2.5cm tungsten cubes. Uniformity was measured by drawing a volume of interest (VOI) within a large water phantom and defined as the standard deviation of voxel values divided by the mean voxel value. Contrast was defined as the peak signals of a set of tungsten cubes divided by the mean voxel value of the water background. SNR was defined as the peak signals of cubes divided by the standard deviation (noise) of the water background. Vertical smearing, i.e. vertical thickness blurring along the zenith axis for a set of 2 cm thick tungsten plates, was defined as the FWHM of vertical spread function for the plate. These image metrics provided a useful tool to quantify the basic imaging properties for muon tomography.
Databáze: OpenAIRE