An apodized-aperture x-ray detector design for improved image quality in mammography

X-ray imaging for early cancer detection, such as screening mammography, requires images with high signal-to-noise ratio (SNR) using low levels of radiation exposure. Conventional detectors consist of a matrix of sensor elements, producing images where each pixel corresponds to a single sensor element. This imposes a fundamental limitation on image contrast and SNR for imaging fine detail for a given exposure. The work presented here reconsiders x-ray image formation using a new x-ray detector design that synthesizes image pixels from a large number of very small sensor elements with the goal of optimizing contrast and SNR. Our new detector design, called apodized-aperture pixel (AAP), makes use of recent technology developments to produce images from an “over-sampled” sensor signal while suppressing both signal and noise aliasing to improve the modulation transfer function (MTF) and detective quantum efficiency (DQE). Signal and noise performance of the AAP approach is described theoretically using a cascaded-systems analysis. This approach preserves the MTF of the small sensor elements up to the image sampling cut-off frequency where the MTF is increased by up to 53%. Frequencies above the cut-off are suppressed, eliminating both signal and noise aliasing artifacts and corresponding to a high-frequency DQE increase by 2.5x. X-ray interactions in a scintillator introduce signal and noise correlations, including x-ray reabsorption and converter blur, resulting in reduced aliasing and decreased improvement in DQE. Best results with the AAP design were obtained using a high-resolution converter, such as selenium (Se), with little impact from reabsorption. Implementation on a Se/CMOS micro-sensor prototype with 7.8\mum element size with image pixel size approximately 50\mum showed a flat DQE curve (ideal) up to 10cycles/mm. AAP images of resolution test patterns, mammography phantoms, and specimen imaging of micro-calcifications from biopsies showed the expected improvements in SNR and visibility of fine-detail. It is concluded that synthesizing image pixels from small physical sensor elements can increase MTF and DQE, and eliminate aliasing artifacts, for a desired image pixel size. The resulting increase in SNR may benefit all forms of radiography, and in particular mammography, where accurate visualization of fine detail is important for early cancer detection

On a wildlife tracking and telemetry system : a wireless network approach

Includes abstract.Includes bibliographical references (p. 239-261).Motivated by the diversity of animals, a hybrid wildlife tracking system, EcoLocate, is proposed, with lightweight VHF-like tags and high performance GPS enabled tags, bound by a common wireless network design. Tags transfer information amongst one another in a multi-hop store-and-forward fashion, and can also monitor the presence of one another, enabling social behaviour studies to be conducted. Information can be gathered from any sensor variable of interest (such as temperature, water level, activity and so on) and forwarded through the network, thus leading to more effective game reserve monitoring. Six classes of tracking tags are presented, varying in weight and functionality, but derived from a common set of code, which facilitates modular tag design and deployment. The link between the tags means that tags can dynamically choose their class based on their remaining energy, prolonging lifetime in the network at the cost of a reduction in function. Lightweight, low functionality tags (that can be placed on small animals) use the capabilities of heavier, high functionality devices (placed on larger animals) to transfer their information. EcoLocate is a modular approach to animal tracking and sensing and it is shown how the same common technology can be used for diverse studies, from simple VHF-like activity research to full social and behavioural research using wireless networks to relay data to the end user. The network is not restricted to only tracking animals – environmental variables, people and vehicles can all be monitored, allowing for rich wildlife tracking studies

Advances in Information Security and Privacy

With the recent pandemic emergency, many people are spending their days in smart working and have increased their use of digital resources for both work and entertainment. The result is that the amount of digital information handled online is dramatically increased, and we can observe a significant increase in the number of attacks, breaches, and hacks. This Special Issue aims to establish the state of the art in protecting information by mitigating information risks. This objective is reached by presenting both surveys on specific topics and original approaches and solutions to specific problems. In total, 16 papers have been published in this Special Issue

Hyper-Kamiokande Design Report

325 pages325 pagesOn the strength of a double Nobel prize winning experiment (Super)Kamiokande and an extremely successful long baseline neutrino programme, the third generation Water Cherenkov detector, Hyper-Kamiokande, is being developed by an international collaboration as a leading worldwide experiment based in Japan. The Hyper-Kamiokande detector will be hosted in the Tochibora mine, about 295 km away from the J-PARC proton accelerator research complex in Tokai, Japan. The currently existing accelerator will be steadily upgraded to reach a MW beam by the start of the experiment. A suite of near detectors will be vital to constrain the beam for neutrino oscillation measurements. A new cavern will be excavated at the Tochibora mine to host the detector. The experiment will be the largest underground water Cherenkov detector in the world and will be instrumented with new technology photosensors, faster and with higher quantum efficiency than the ones in Super-Kamiokande. The science that will be developed will be able to shape the future theoretical framework and generations of experiments. Hyper-Kamiokande will be able to measure with the highest precision the leptonic CP violation that could explain the baryon asymmetry in the Universe. The experiment also has a demonstrated excellent capability to search for proton decay, providing a significant improvement in discovery sensitivity over current searches for the proton lifetime. The atmospheric neutrinos will allow to determine the neutrino mass ordering and, together with the beam, able to precisely test the three-flavour neutrino oscillation paradigm and search for new phenomena. A strong astrophysical programme will be carried out at the experiment that will detect supernova neutrinos and will measure precisely solar neutrino oscillation

Testing of Materials and Elements in Civil Engineering

This book was proposed and organized as a means to present recent developments in the field of testing of materials and elements in civil engineering. For this reason, the articles highlighted in this editorial relate to different aspects of testing of different materials and elements in civil engineering, from building materials to building structures. The current trend in the development of testing of materials and elements in civil engineering is mainly concerned with the detection of flaws and defects in concrete elements and structures, and acoustic methods predominate in this field. As in medicine, the trend is towards designing test equipment that allows one to obtain a picture of the inside of the tested element and materials. Interesting results with significance for building practices were obtained

Scheduling Classifiers for Real-Time Hazard Perception Considering Functional Uncertainty

This paper addresses the problem of real-time classification-based machine perception, exemplified by a mobile autonomous system that must continually check that a designated area ahead is free of hazards. Such hazards must be identified within a specified time. In practice, classifiers are imperfect; they exhibit functional uncertainty. In the majority of cases, a given classifier will correctly determine whether there is a hazard or the area ahead is clear. However, in other cases it may produce false positives, i.e. indicate hazard when the area is clear, or false negatives, i.e. indicate clear when there is in fact a hazard. The former are undesirable since they reduce quality of service, whereas the latter are a potential safety concern. A stringent constraint is therefore placed on the maximum permitted probability of false negatives. Since this requirement may not be achievable using a single classifier, one approach is to (logically) OR the outputs of multiple disparate classifiers together, setting the final output to hazard if any of the classifiers indicates hazard. This reduces the probability of false negatives; however, the trade-off is an inevitably increase in the probability of false positives and an increase in the overall execution time required. In this paper, we provide optimal algorithms for the scheduling of classifiers that minimize the probability of false positives, while meeting both a latency constraint and a constraint on the maximum acceptable probability of false negatives. The classifiers may have arbitrary statistical dependences between their functional behaviors (probabilities of correct identification of hazards), as well as variability in their execution times, characterized by typical and worst-case values