Methods based on magnetic resonance imaging for the measurement of three-dimensional distributions of radiation dose are highly developed. However, relatively little work has been done on optical computed tomography (OCT). This paper describes a new OCT scanner based on a broad beam light source and a two-dimensional charge-coupled device (CCD) detector. A number of key design features are discussed including the light source; the scanning tank, turntable and stepper motor control; the diffuser screen onto which images are projected and the detector. It is shown that the non-uniform pixel sensitivity of the low-cost CCD detector used and the granularity of the diffuser screen lead to a serious ring artefact in the reconstructed images. Methods are described for eliminating this. The problems arising from reflection and refraction at the walls of the gel container are explained. Optical ray-tracing simulations are presented for cylindrical containers with a variety of radii and verified experimentally. Small changes in the model parameters lead to large variations in the signal intensity observed in the projection data. The effect of imperfect containers on data quality is discussed and a method based on a 'correction scan' is shown to be successful in correcting many of the related image artefacts. The results of two tomography experiments are presented. In the first experiment, a radiochromic Fricke gel sample was exposed four times in different positions to a 100 kVp x-ray beam perpendicular to the plane of imaging. Images of absorbed dose with slice thickness of 140 microm were acquired. with 'true' in-plane resolution of 560 x 560 microm2 at the edge of the 72 mm field of view and correspondingly higher resolution at the centre. The nominal doses measured correlated well with the known exposure times. The second experiment demonstrated the well known phenomenon of diffusion in the dosemeter gels and yielded a value of (0.12 +/- 0.02) mm2 s(-1) for the diffusion coefficient of the xylenol orange/iron complex. Finally, the overall implications of the above findings for dosimetry using OCT are discussed.
Flat-panel imagers consisting of the first large area, self-scanning, pixelated, solid-state arrays made with hydrogenated amorphous silicon (a-Si:H) are under development by the authors for applications in diagnostic x-ray and megavoltage radiotherapy imaging. The arrays, designated by the acronym MASDA for multi-element amorphous silicon detector array, consist of a two-dimensional array of a-Si:H photodiodes and thin-film transistors and are used in conjunction with scintillating materials. Imagers utilizing MASDA arrays offer a variety of advantages over existing technologies. This article presents initial megavoltage and diagnostic-quality x-ray images taken with several such arrays including the first examples of anatomical-phantom images. The external readout electronics and imaging techniques required to obtain such images are outlined, the construction, operation, and advantages of the arrays briefly reviewed, and the future potential of this new technology discussed.
Non-intrusive inspection systems based on X-ray radiography techniques are routinely used at transport hubs to ensure the conformity of cargo content with the supplied shipping manifest. As trade volumes increase and regulations become more stringent, manual inspection by trained operators is less and less viable due to low throughput. Machine vision techniques can assist operators in their task by automating parts of the inspection workflow. Since cars are routinely involved in trafficking, export fraud, and tax evasion schemes, they represent an attractive target for automated detection and flagging for subsequent inspection by operators. In this contribution, we describe a method for the detection of cars in X-ray cargo images based on trained-from-scratch Convolutional Neural Networks. By introducing an oversampling scheme that suitably addresses the low number of car images available for training, we achieved 100% car image classification rate for a false positive rate of 1-in-454. Cars that were partially or completely obscured by other goods, a modus operandi frequently adopted by criminals, were correctly detected. We believe that this level of performance suggests that the method is suitable for deployment in the field. It is expected that the generic object detection workflow described can be extended to other object classes given the availability of suitable training data.
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