Paper ID | SS-CIMM.7 | ||
Paper Title | Hyperspectral Neutron CT with Material Decomposition | ||
Authors | Thilo Balke, Purdue University, United States; Alexander Makenzie Long, Sven Vogel, Brendt Wohlberg, Los Alamos National Laboratory, United States; Charles Bouman, Purdue University, United States | ||
Session | SS-CIMM: Special Session: Computational Imaging for Materials and Microscopy | ||
Location | Area B | ||
Session Time: | Monday, 20 September, 13:30 - 15:00 | ||
Presentation Time: | Monday, 20 September, 13:30 - 15:00 | ||
Presentation | Poster | ||
Topic | Special Sessions: Computational Imaging for Materials and Microscopy | ||
IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
Abstract | Energy resolved neutron imaging (ERNI) is an advanced neutron radiography technique capable of non-destructively extracting spatial isotopic information within a given material. Energy-dependent radiography image sequences can be created by utilizing neutron time-of-flight techniques. In combination with uniquely characteristic isotopic neutron crosssection spectra, isotopic areal densities can be determined on a per-pixel basis, thus resulting in a set of areal density images for each isotope present in the sample. By preforming ERNI measurements over several rotational views, an isotope decomposed 3D computed tomograpy is possible. We demonstrate a method involving a robust and automated background estimation based on a linear programming formulation. The extremely high noise due to low count measurements is overcome using a sparse coding approach. It allows for a significant computation time improvement, from weeks to a few hours compared to existing neutron evaluation tools, enabling at the present stage a semi-quantitative, user-friendly routine application. |