A new Computed Tomography (CT) detector with color/dual-energy features and substantially reduced patient X-ray dose

Computed Tomography (CT) is one of the most important medical diagnosis tools of today. World-wide there is a waste number of installations, a strong increase in sales, and it represents consequently a big industry for the manufacturers. The X-ray detecto r in the CT is the main part of the machine, and represents a very significant business by itself. There is currently a growing demand for new X-ray detector technology that can reduce patient radiation dose and have the additional feature of tissue compo sitional analysis (material decomposition). One of the largest CT manufacturers (NN) has in collaboration with Interon, extensively been testing an early prototype made by us. Based on this early prototype and the continued high interest from NN, we want in this project to develop a new CT detector module that includes both of the above mentioned CT advances as well as meeting all the other high standards of today's CT machines. Specifically, we want to develop a CT detector module which will be capable of handling an X-ray input flux of up to 108 counts per second per mm2 surface area for all pixels through X-ray counting in colors. The module will comprise two CdTe sensors, of up to 1024 pixels, each connected to an ASIC with the corresponding number o f processing channels. These two parts will be packaged in a ball-grid-array (BGA) that is supported with auxiliary electronics and mechanical packaging. The entire module will be retrofit-able as a plug-in to the newest version CT machine of NN. The enti re CT detector of this machine will comprise about 50 detector modules arranged in a densely packed array. The final achievement of the project will be to build the modules needed for NN to build and install the entire detector into their machine dedicate d for this in order to perform full testing and demonstrations. The project will be performed by Interon (responsible), the University of Oslo, DxRay Inc., NN, CERN and the University of California, Santa Barbara