Performance evaluation of detectors for digital radiography

To date the hospital radiological workflow is completing a transition from analog to digital technology. Since the X-rays digital detection technologies have become mature, hospitals are trading on the natural devices turnover to replace the conventional screen film devices with digital ones. The transition process is complex and involves not just the equipment replacement but also new arrangements for image transmission, display (and reporting) and storage. This work is focused on 2D digital detector’s characterization with a concern to specific clinical application; the systems features linked to the image quality are analyzed to assess the clinical performances, the conversion efficiency, and the minimum dose necessary to get an acceptable image. The first section overviews the digital detector technologies focusing on the recent and promising technological developments. The second section contains a description of the characterization methods considered in this thesis categorized in physical, psychophysical and clinical; theory, models and procedures are described as well. The third section contains a set of characterizations performed on new equipments that appears to be some of the most advanced technologies available to date. The fourth section deals with some procedures and schemes employed for quality assurance programs.

Matrix Designs and Methods for Secure and Efficient Compressed Sensing

The idea of balancing the resources spent in the acquisition and encoding of natural signals strictly to their intrinsic information content has interested nearly a decade of research under the name of compressed sensing. In this doctoral dissertation we develop some extensions and improvements upon this technique's foundations, by modifying the random sensing matrices on which the signals of interest are projected to achieve different objectives. Firstly, we propose two methods for the adaptation of sensing matrix ensembles to the second-order moments of natural signals. These techniques leverage the maximisation of different proxies for the quantity of information acquired by compressed sensing, and are efficiently applied in the encoding of electrocardiographic tracks with minimum-complexity digital hardware. Secondly, we focus on the possibility of using compressed sensing as a method to provide a partial, yet cryptanalysis-resistant form of encryption; in this context, we show how a random matrix generation strategy with a controlled amount of perturbations can be used to distinguish between multiple user classes with different quality of access to the encrypted information content. Finally, we explore the application of compressed sensing in the design of a multispectral imager, by implementing an optical scheme that entails a coded aperture array and Fabry-Pérot spectral filters. The signal recoveries obtained by processing real-world measurements show promising results, that leave room for an improvement of the sensing matrix calibration problem in the devised imager.