Colin Esbrand

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.

I-ImaS: intelligent imaging sensors

Conventional x-radiography uniformly irradiates the relevant region of the patient. Across that region, however, there is likely to be significant variation in both the thickness and pathological composition of the tissues present, which means that the x-ray exposure conditions selected, and consequently the image quality achieved, are a compromise. The I-ImaS concept eliminates this compromise by intelligently scanning the patient to identify the important diagnostic features, which are then used to adaptively control the x-ray exposure conditions at each point in the patient. In this way optimal image quality is achieved throughout the region of interest whilst maintaining or reducing the dose. An I-ImaS system has been built under an EU Framework 6 project and has undergone pre-clinical testing. The system is based upon two rows of sensors controlled via an FPGA based DAQ board. Each row consists of a 160 mm ? 1 mm linear array of ten scintillator coated 3T CMOS APS devices with 32 ?m pixels and a readable array of 520 ? 40 pixels. The first sensor row scans the patient using a fraction of the total radiation dose to produce a preview image, which is then interrogated to identify the optimal exposure conditions at each point in the image. A signal is then sent to control a beam filter mechanism to appropriately moderate x-ray beam intensity at the patient as the second row of sensors follows behind. Tests performed on breast tissue sections found that the contrast-to-noise ratio in over 70% of the images was increased by an average of 15% at an average dose reduction of 9%. The same technology is currently also being applied to baggage scanning for airport security.

The implementation of CMOS sensors within a real time digital mammography intelligent imaging system: The I-ImaS System

The integration of technology with healthcare has undoubtedly propelled the medical imaging sector well into the twenty first century. The concept of digital imaging introduced during the 1970s has since paved the way for established imaging techniques where digital mammography, phase contrast imaging and CT imaging are just a few examples. This paper presents a prototype intelligent digital mammography system designed and developed by a European consortium. The final system, the I-ImaS system, utilises CMOS monolithic active pixel sensor (MAPS) technology promoting on-chip data processing, enabling the acts of data processing and image acquisition to be achieved simultaneously; consequently, statistical analysis of tissue is achievable in real-time for the purpose of x-ray beam modulation via a feedback mechanism during the image acquisition procedure. The imager implements a dual array of twenty 520 pixel × 40 pixel CMOS MAPS sensing devices with a 32μm pixel size, each individually coupled to a 100μm thick thallium doped structured CsI scintillator. This paper presents the first intelligent images of real breast tissue obtained from the prototype system of real excised breast tissue where the x-ray exposure was modulated via the statistical information extracted from the breast tissue itself. Conventional images were experimentally acquired where the statistical analysis of the data was done off-line, resulting in the production of simulated real-time intelligently optimised images. The results obtained indicate real-time image optimisation using the statistical information extracted from the breast as a means of a feedback mechanisms is beneficial and foreseeable in the near future.