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 setting

CMOS Monolithic Active Pixel Sensors (MAPS): Developments and future outlook

Re-invented in the early 1990s, on both sides of the Atlantic, Monolithic Active Pixel Sensors (MAPS) in a CMOS technology are today the most sold solid-state imaging devices, overtaking the traditional technology of Charge-Coupled Devices (CCD). The slow uptake of CMOS MAPS started with low-end applications, for example web-cams, and is slowly pervading the high-end applications, for example in prosumer digital cameras. Higher specifications are required for scientific applications: very low noise, high speed, high dynamic range, large format and radiation hardness are some of these requirements. This paper will present a brief overview of the CMOS Image Sensor technology and of the requirements for scientific applications. As an example, a sensor for X-ray imaging will be presented. This sensor was developed within a European FP6 Consortium, intelligent imaging sensors (I-ImaS). © 2007 Elsevier B.V. All rights reserved

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

CMOS Monolithic Active Pixel Sensors (MAPS): developments and future outlook

Re-invented in the early 1990s, on both sides of the Atlantic, Monolithic Active Pixel Sensors (MAPS) in a CMOS technology are today the most sold solid-state imaging devices, overtaking the traditional technology of Charge-Coupled Devices (CCD). The slow uptake of CMOS MAPS started with low-end applications, for example web-cams, and is slowly pervading the high-end applications, for example in prosumer digital cameras. Higher specifications are required for scientific applications: very low noise, high speed, high dynamic range, large format and radiation hardness are some of these requirements. This paper will present a brief overview of the CMOS Image Sensor technology and of the requirements for scientific applications. As an example, a sensor for X-ray imaging will be presented. This sensor was developed within a European FP6 Consortium, intelligent imaging sensors (I-ImaS)

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