Abstract
Modern developments of gamma-ray imagers by integrating multi-contextual sensors and advanced computer vision theories have enabled unprecedented capabilities in detection and imaging, reconstruction and mapping of radioactive sources. Notwithstanding these remarkable capabilities, the addition of multiple sensors such as light detection and ranging units (LiDAR), RGB-D sensors (Microsoft Kinect), and inertial measurement units (IMU) are mostly expensive. Instead of using such expensive sensors, we, in this paper, introduce a modest three-dimensional (3D) gamma-ray imaging method by exploiting the advancements in modern stereo vision technologies. A stereo line equation model is proposed to properly identify the distribution area of gamma-ray intensities that are used for two-dimensional (2D) visualizations. Scene data information of the surrounding environment captured at different locations are reconstructed by re-projecting disparity images created with the semi-global matching algorithm (SGM) and are merged together by employing the point-to-point iterative closest point algorithm (ICP). Instead of superimposing/overlaying 2D radioisotopes on the merged scene area, reconstructions of 2D gamma images are fused together with it to create a detailed 3D volume. Through experimental results, we try to emphasize the accuracy of our proposed fusion method.
Highlights
Detecting and imaging, localizing and volumetric-visualizing; gamma-ray sources are of the actively discussed topics in the field of radiology, since the discovery of X-rays in late 1895 [1]
The detector is composed of a NaI(Tl) scintillator hybridized with a Hamamatsu H10722 small photo-multiplier tube, a 10 mm diameter pinhole-type Lead (Pb) collimator, and a Tungsten (W) radiation shield case (Fig. 2)
Reconstruction and time complexity results of our method are qualitatively compared with the results obtained by the block matching algorithm [31] in OpenCV library [30]
Summary
Detecting and imaging, localizing and volumetric-visualizing; gamma-ray sources are of the actively discussed topics in the field of radiology, since the discovery of X-rays in late 1895 [1]. The biggest challenge of most of these imagers is the correct differentiation between relevant and irrelevant information used to identify source intensities with scene data. Though the use of Geiger counters had gradually increased; mainly after the incident in Fukushima, but they resulted in many wrong claims of radiation contamination. They lack the ability to discriminate background radiation from the radioactivity [1]
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