J. Leaver

The CMS tracker readout front end driver

The front end driver is a 9U 400mm VME64x card designed for reading out the CMS silicon tracker signals transmitted by the APV25 analogue pipeline ASICs. The FED receives the signals via 96 optical fibers at a total input rate of 3.4 GBytes/sec. The signals are digitized and processed by applying algorithms for pedestal and common mode noise subtraction. Algorithms that search for clusters of hits are used to further reduce the input rate. Only the cluster data along with trigger information of the event are transmitted to the CMS DAQ system using the S-LINK64 protocol at a maximum rate of 400 Mbytes/sec. All data processing algorithms on the FED are executed in large on-board FPGAs. Results on the design, performance, testing and quality control of the FED are presented and discussed.

Adaptive Imaging Using the I-ImaS X-Ray Imaging System

The I-ImaS (intelligent imaging sensors) is an European Union project whose objective is to design and develop intelligent imaging sensors and evaluate their use within an adaptive imaging system. The system employs an in-line scanning technology approach and use of CMOS active pixel sensors developed specifically for high spatial resolution, efficient light collection and large dynamic range. This paper discusses the principle of the data acquisition (DAQ) system and the characterisation of the I-ImaS sensors, both optically and using mono-energetic X-rays.

A Multi-Element Detector System for Intelligent Imaging: I-ImaS

I-ImaS is a European project aiming to produce new, intelligent X-ray imaging systems using novel APS sensors to create optimal diagnostic images. Initial systems concentrate on mammography and encephalography. Later development will yield systems for other types of radiography such as industrial QA and homeland security. The I-ImaS system intelligence, due to APS technology and FPGAs, allows real-time analysis of data during image acquisition, giving the capability to build a truly adaptive imaging system with the potential to create images with maximum diagnostic information within given dose constraints. A companion paper deals with the DAQ system and preliminary characterization. This paper considers the laboratory X-ray characterization of the detector elements of the I-ImaS system. The characterization of the sensors when tiled to form a strip detector will be discussed, along with the appropriate correction techniques formulated to take into account the misalignments between individual sensors within the array. Preliminary results show that the detectors have sufficient performance to be used successfully in the initial mammographic and encephalographic I-ImaS systems under construction and this paper will further discuss the testing of these systems and the iterative processes used for intelligence upgrade in order to obtain the optimal algorithms and settings.

Adaptive image content-based exposure control for scanning applications in radiography

I-ImaS (Intelligent Imaging Sensors) is a European project which has designed and developed a new adaptive X-ray imaging system using on-line exposure control, to create locally optimized images. The I-ImaS system allows for real-time image analysis during acquisition, thus enabling real-time exposure adjustment. This adaptive imaging system has the potential of creating images with optimal information within a given dose constraint and to acquire optimally exposed images of objects with variable density during one scan. In this paper we present the control system and results from initial tests on mammographic and encephalographic images. Furthermore, algorithms for visualization of the resulting images, consisting of unevenly exposed image regions, are developed and tested. The preliminary results show that the same image quality can be achieved at 30-70% lower dose using the I-ImaS system compared to conventional mammography systems.

A scanning system for intelligent imaging: I-ImaS

I-ImaS (Intelligent Imaging Sensors) is a European project aiming to produce adaptive x-ray imaging systems using Monolithic Active Pixel Sensors (MAPS) to create optimal diagnostic images. Initial systems concentrate on mammography and cephalography. The on-chip intelligence available to MAPS technology will allow real-time analysis of data during image acquisition, giving the capability to build a truly adaptive imaging system with the potential to create images with maximum diagnostic information within given dose constraints. In our system, the exposure in each image region is optimized and the beam intensity is a function not only of tissue thickness and attenuation, but also of local physical and statistical parameters found in the image itself. Using a linear array of detectors with on-chip intelligence, the system will perform an on-line analysis of the image during the scan and then will optimize the X-ray intensity in order to obtain the maximum diagnostic information from the region of interest while minimizing exposure of less important, or simply less dense, regions. This paper summarizes the testing of the sensors and their electronics carried out using synchrotron radiation, x-ray sources and optical measurements. The sensors are tiled to form a 1.5D linear array. These have been characterised and appropriate correction techniques formulated to take into account misalignments between individual sensors. Full testing of the mammography and cephalography I-ImaS prototypes is now underway and the system intelligence is constantly being upgraded through iterative testing in order to obtain the optimal algorithms and settings.

Design and Characterization of the I-ImaS Multi-Element X-Ray Detector System

I-ImaS (Intelligent Imaging Sensors) is a European project aiming to produce new, intelligent X-ray imaging systems using novel APS sensors to create optimal diagnostic images. Initial systems have been constructed for medical imaging; specifically mammography and dental encephalography. However, the I-ImaS system concept could be applied to all areas of X-ray imaging, including homeland security and industrial QA. The I-ImaS system intelligence is implemented by the use of APS technology and FPGAs, allowing real-time analysis of data during image acquisition. This gives the system the capability to perform as an on-the-fly adaptive imaging system, with the potential to create images with maximum diagnostic information within given dose constraints. The I-ImaS system uses a scanning linear array of scintillator-coupled 1.5-D CMOS Active Pixel Sensors to create a full 2-D X-ray image of an object. This paper describes the parameters considered when choosing the scintillator elements of the detectors. A study of the positioning of the sensors to form a linear detector is also considered, along with a discussion of the potential losses in image quality associated with creating a linear sensor by tiling many smaller sensors. Preliminary results show that the detectors have sufficient performance to be used successfully in the initial mammographic and encephalographic I-ImaS systems that are currently under construction.

Characterisation of the Components of a Prototype Scanning Intelligent Imaging System for Use in Digital Mammography: The I-ImaS System

The physical performance characteristics of a prototype scanning digital mammography (DM) system have been investigated. The I-ImaS system utilises CMOS MAPS technology promoting on-chip data processing; consequently statistical analysis is therefore achievable in real-time for the purpose of exposure modulation via a feedback mechanism during the image acquisition procedure. The imager employs a dual array of twenty CMOS APS sensing devices each individually coupled to a 100 mum thick thallium doped structured CsI scintillator. The X-ray performance of the sensors was characterised where the presampled modulation transfer function (MTF), normalised noise power spectrum (NNPS), and the detective quantum efficiency (DQE) was determined. The presampled MTF was measured utilising the slit technique and was found to be 0.1 at 6 lp/mm. The NNPS measured utilising a W/Al target/filter combination hardened with 38 mm PMMA was seen to decrease with increasing exposure as expected and the manifesting DQE was 0.30 at close to zero spatial frequency at an exposure of 1.75 mR. Preliminary image stitching of the individual steps acquired from the scanning system is presented. A conventionally acquired image that is without the implementation of beam modulation or off-line intelligence is compared and contrasted to an intelligently off-line processed image. Results indicate the implementation of real-time intelligence into the image acquisition phase of digital mammography is foreseeable.