An image reconstruction algorithm based on three-dimensional DBSCAN for energy-resolved neutron imaging

Backgroup Energy-resolved neutron imaging is an effective method to investigate the crystal structure and stress distribution of materials. The energy-resolved neutron imaging instrument (ERNI) has been established at China Spallation Neutron Source (CSNS). An energy-resolved neutron imaging detector based on the high-speed camera TPX3Cam is used at ERNI to achieve neutron energy resolution by recording time-of-flight (ToF) of neutrons. TPX3Cam records the photon events emitted by the neutron absorption in the scintillator. An image reconstruction algorithm is needed to reconstruct the neutron events to improve the spatial and energy resolution of the detector.
Purpose The data output from the TPX3Cam contains photon events that dispersion in space and time. We want to develop an image reconstruction algorithm to identify photon events produced by a single neutron and remove the gamma ray as well as the noise. Finally, better spatial resolution and energy resolution can be obtained by neutron events reconstruction.
Method Image reconstruction algorithms involves photon events clustering and neutron events reconstruction. Based on the traditional two-dimensional density-based spatial clustering of applications with noise (DBSCAN) algorithm, the three-dimensional DBSCAN algorithm is developed including ToF as the third dimension of information. The precision of Bragg edge of a sample is related to the energy resolution of the detector; thus, the quality of the parameters can be evaluated by the improvement in Bragg edge precision after reconstruction.
Result and conclusion The three-dimensional DBSCAN algorithm can proceed the image data effectively and identify the neutron events and noise. The precision of reconstructed Bragg edges is improved from 3.601‰ to 3.337‰, and the spatial resolution is improved from 150 µm/line width to 100 µm/line width.