Kevin Wells

A review of X-ray explosives detection techniques for checked baggage.

In recent times, the security focus for civil aviation has shifted from hijacking in the 1980s, towards deliberate sabotage. X-ray imaging provides a major tool in checked baggage inspection, with various sensitive techniques being brought to bear in determining the form, and density of items within luggage as well as other material dependent parameters. This review first examines the various challenges to X-ray technology in securing a safe system of passenger transportation. An overview is then presented of the various conventional and less conventional approaches that are available to the airline industry, leading to developments in state-of-the-art imaging technology supported by enhanced machine and observer-based decision making principles.

Digital autoradiography using room temperature CCD and CMOS imaging technology

CCD (charged coupled device) and CMOS imaging technologies can be applied to thin tissue autoradiography as potential imaging alternatives to using conventional film. In this work, we compare two particular devices: a CCD operating in slow scan mode and a CMOS-based active pixel sensor, operating at near video rates. Both imaging sensors have been operated at room temperature using direct irradiation with images produced from calibrated microscales and radiolabelled tissue samples. We also compare these digital image sensor technologies with the use of conventional film. We show comparative results obtained with (14)C calibrated microscales and (35)S radiolabelled tissue sections. We also present the first results of (3)H images produced under direct irradiation of a CCD sensor operating at room temperature. Compared to film, silicon-based imaging technologies exhibit enhanced sensitivity, dynamic range and linearity.

A quantitative assessment of using the Kinect for Xbox 360 for respiratory surface motion tracking

This paper describes a quantitative assessment of the Microsoft Kinect for X-box360TM for potential application in tracking respiratory and body motion in diagnostic imaging and external beam radiotherapy. However, the results can also be used in many other biomedical applications. We consider the performance of the Kinect in controlled conditions and find mm precision at depths of 0.8-1.5m. We also demonstrate the use of the Kinect for monitoring respiratory motion of the anterior surface. To improve the performance of respiratory monitoring, we fit a spline model of the chest surface through the depth data as a method of a marker-less monitoring of a respiratory motion. In addition, a comparison between the Kinect camera with and without zoom lens and a marker-based system was used to evaluate the accuracy of using the Kinect camera as a respiratory tracking system.

Conversion of mammographic images to appear with the noise and sharpness characteristics of a different detector and x-ray system

PURPOSE Undertaking observer studies to compare imaging technology using clinical radiological images is challenging due to patient variability. To achieve a significant result, a large number of patients would be required to compare cancer detection rates for different image detectors and systems. The aim of this work was to create a methodology where only one set of images is collected on one particular imaging system. These images are then converted to appear as if they had been acquired on a different detector and x-ray system. Therefore, the effect of a wide range of digital detectors on cancer detection or diagnosis can be examined without the need for multiple patient exposures. METHODS Three detectors and x-ray systems [Hologic Selenia (ASE), GE Essential (CSI), Carestream CR (CR)] were characterized in terms of signal transfer properties, noise power spectra (NPS), modulation transfer function, and grid properties. The contributions of the three noise sources (electronic, quantum, and structure noise) to the NPS were calculated by fitting a quadratic polynomial at each spatial frequency of the NPS against air kerma. A methodology was developed to degrade the images to have the characteristics of a different (target) imaging system. The simulated images were created by first linearizing the original images such that the pixel values were equivalent to the air kerma incident at the detector. The linearized image was then blurred to match the sharpness characteristics of the target detector. Noise was then added to the blurred image to correct for differences between the detectors and any required change in dose. The electronic, quantum, and structure noise were added appropriate to the air kerma selected for the simulated image and thus ensuring that the noise in the simulated image had the same magnitude and correlation as the target image. A correction was also made for differences in primary grid transmission, scatter, and veiling glare. The method was validated by acquiring images of a CDMAM contrast detail test object (Artinis, The Netherlands) at five different doses for the three systems. The ASE CDMAM images were then converted to appear with the imaging characteristics of target CR and CSI detectors. RESULTS The measured threshold gold thicknesses of the simulated and target CDMAM images were closely matched at normal dose level and the average differences across the range of detail diameters were -4% and 0% for the CR and CSI systems, respectively. The conversion was successful for images acquired over a wide dose range. The average difference between simulated and target images for a given dose was a maximum of 11%. CONCLUSIONS The validation shows that the image quality of a digital mammography image obtained with a particular system can be degraded, in terms of noise magnitude and color, sharpness, and contrast to account for differences in the detector and antiscatter grid. Potentially, this is a powerful tool for observer studies, as a range of image qualities can be examined by modifying an image set obtained at a single (better) image quality thus removing the patient variability when comparing systems.

DynAMITe: a wafer scale sensor for biomedical applications

In many biomedical imaging applications Flat Panel Imagers (FPIs) are currently the most common option. However, FPIs possess several key drawbacks such as large pixels, high noise, low frame rates, and excessive image artefacts. Recently Active Pixel Sensors (APS) have gained popularity overcoming such issues and are now scalable up to wafer size by appropriate reticule stitching. Detectors for biomedical imaging applications require high spatial resolution, low noise and high dynamic range. These figures of merit are related to pixel size and as the pixel size is fixed at the time of the design, spatial resolution, noise and dynamic range cannot be further optimized. The authors report on a new rad-hard monolithic APS, named DynAMITe (Dynamic range Adjustable for Medical Imaging Technology), developed by the UK MI-3 Plus consortium. This large area detector (12.8 cm × 12.8 cm) is based on the use of two different diode geometries within the same pixel array with different size pixels (50 μm and 100 μm). Hence the resulting device can possess two inherently different resolutions each with different noise and saturation performance. The small and the large pixel cameras can be reset at different voltages, resulting in different depletion widths. The larger depletion width for the small pixels allows the initial generated photo-charge to be promptly collected, which ensures an intrinsically lower noise and higher spatial resolution. After these pixels reach near saturation, the larger pixels start collecting so offering a higher dynamic range whereas the higher noise floor is not important as at higher signal levels performance is governed by the Poisson noise of the incident radiation beam. The overall architecture and detailed characterization of DynAMITe will be presented in this paper.

The performance of a CCD digital autoradiography imaging system

Autoradiography is a widely used technique for imaging trace quantities of radioactivity within biological samples, conventionally using photographic film. This method produces images with high spatial resolution, but it suffers from very low sensitivity and poor dynamic range. Digital autoradiography systems with greatly improved sensitivity and linearity are commercially available, but the spatial resolution is usually much less than that achieved using film. We report here the design, construction and characterization of a novel digital autoradiography system based on scientific-grade charged coupled devices (CCDs). Images of x-ray and beta emissions from radionuclides commonly used in autoradiography show that the system can perform high-speed quantitative imaging with a spatial resolution of approximately 30, microm. Using a frame by frame acquisition method the dynamic range is shown to be at least three orders of magnitude. The absolute detection efficiency is comparable to the best of the currently available digital systems. CCD images of 125I and 14C radioisotope distributions in tissue samples are superior to the equivalent film images and have been acquired in 1-10% of the time.

Simulation and assessment of realistic breast lesions using fractal growth models

A new method of generating realistic three dimensional simulated breast lesions known as diffusion limited aggregation (DLA) is presented, and compared with the random walk (RW) method. Both methods of lesion simulation utilize a physics-based method for inserting these simulated lesions into 2D clinical mammogram images that takes into account the polychromatic x-ray spectrum, local glandularity and scatter. DLA and RW masses were assessed for realism via a receiver operating characteristic (ROC) study with nine observers. The study comprised 150 images of which 50 were real pathology proven mammograms, 50 were normal mammograms with RW inserted masses and 50 were normal mammograms with DLA inserted masses. The average area under the ROC curve for the DLA method was 0.55 (95% confidence interval 0.51-0.59) compared to 0.60 (95% confidence interval 0.56-0.63) for the RW method. The observer study results suggest that the DLA method produced more realistic masses with more variability in shape compared to the RW method. DLA generated lesions can overcome the lack of complexity in structure and shape in many current methods of mass simulation.

A Particle Filter Approach to Respiratory Motion Estimation in Nuclear Medicine Imaging

With the continual improvement in spatial resolution of Nuclear Medicine (NM) scanners, it has become increasingly important to accurately compensate for patient motion during image acquisition. Respiratory motion produced by normal lung ventilation is a major source of artefacts in NM emission imaging that can affect large parts of the abdominal thoracic cavity. As such, a particle filter (PF) is proposed as a powerful method for motion correction in emission imaging which can successfully account for previously unseen motion. This paper explores a basic PF approach and demonstrates that it is possible to estimate temporally non-stationary motion using training data consisting of only a single respiratory cycle. Evaluation using the XCAT phantom suggests that the PF is a highly promising approach, and can appropriately handle the complex data that arises in clinical situations.

PETRRA: preliminary experimental results from the first full size detector and dead time simulation of the count rate performance of a unique whole body PET camera

The design and construction of the first of two BaF/sub 2/-TMAE large area detectors to be incorporated in a unique double headed whole body PET system (PETRRA) has been completed. Preliminary experimental work carried out with the first large area detector shows an absolute detection efficiency of 20.5% and a time resolution of 3.5 ns (FWHM) and 8.0 ns (FWTM), using 8 mm thick scintillation crystals. An analytical model of the electronic read-out system has been developed to investigate the rate capability of the new scanner. This model predicts that under typical imaging conditions, with 40 MBq of activity in the field of view, the proposed scanner will acquire coincidence data at 20-25 kcps. >

Marker-less respiratory motion modeling using the Microsoft Kinect for Windows

Patient respiratory motion is a major problem during external beam radiotherapy of the thoracic and abdominal regions due to the associated organ and target motion. In addition, such motion introduces uncertainty in both radiotherapy planning and delivery and may potentially vary between the planning and delivery sessions. The aim of this work is to examine subject-specific external respiratory motion and its associated drift from an assumed average cycle which is the basis for many respiratory motion compensated applications including radiotherapy treatment planning and delivery. External respiratory motion data were acquired from a group of 20 volunteers using a marker-less 3D depth camera, Kinect for Windows. The anterior surface encompassing thoracic and abdominal regions were subject to principal component analysis (PCA) to investigate dominant variations. The first principal component typically describes more than 70% of the motion data variance in the thoracic and abdominal surfaces. Across all of the subjects used in this study, 58% of subjects demonstrate largely abdominal breathing and 33% exhibited largely thoracic dominated breathing. In most cases there is observable drift in respiratory motion during the 300s capture period, which is visually demonstrated using Kernel Density Estimation. This study demonstrates that for this cohort of apparently healthy volunteers, there is significant respiratory motion drift in most cases, in terms of amplitude and relative displacement between the thoracic and abdominal respiratory components. This has implications for the development of effective motion compensation methodology.