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We report on the architecture of the System-on-Module (SoM) developed by our group for miniPET-II, the second version of our small animal PET scanner. The paper describes the hardware and software implementation details of the SoM we realized inside the miniPET-II detector module, the embedded Linux operation system, and the the initial results of bandwidth test measurements on the assembled SoM. Detailed description is given on the interfacing of the updated miniPET IP Core to the SoM, on the efficient data transfer method that implements device-to-device DMA transfer, and on the usage of User Datagram Protocol (UDP/IP) for high speed data transfer., QC 20141125

Iterative reconstruction methods are commonly used to obtain images with high resolution and good signal-to-noise ratio in nuclear imaging. The aim of this work was to develop a scalable, fast, cluster based, fully 3-D iterative image reconstruction package for our small animal PET camera, the miniPET. The reconstruction package is developed to determine the 3-D radioactivity distribution from list mode type of data sets and it can also simulate noise-free projections of digital phantoms. We separated the system matrix generation and the fully 3-D iterative reconstruction process. As the detector geometry is fixed for a given camera, the system matrix describing this geometry is calculated only once and used for every image reconstruction, making the process much faster. The Poisson and the random noise sensitivity of the ML-EM iterative algorithm were studied for our small animal PET system with the help of the simulation and reconstruction tool. The reconstruction tool has also been tested with data collected by the miniPET from a line and a cylinder shaped phantom and also a rat., Accepted 2006Published 2007QC20100720

Engineers specialized in multimodal tomography regularly face a wide scale of programming tasks requiring an integrated software system to ensure cost efficiency. Accordingly, a software development framework has been worked out comprising libraries for cluster-based data acquisition, image reconstruction, management of data files and complex multimodal volumetric visualization. This framework enabled us to develop complex software for our miniPET project [1]. This software contains a graphical application integrating data acquisition, cluster monitoring, event sorting, image reconstruction, interactive image processing tools for advanced multimodal visualization. It also contains utilities to solve these tasks without graphical user interface. The components of our acquisition program can run on embedded Linux systems making new ways to develop any other types of data acquisition software that uses embedded Linux systems. A versatile development framework is developed containing specific libraries and special file formats that support multimodal tomography. This framework was successfully used to elaborate our complex miniPET software., QC 20141106

We present a new detector module developed for miniPET-II, the second generation of the miniPET small animal PET scanners. The improved module features new hardware components for better performance: LySO crystal material, increased number of crystal segments, Hamamatsu H9500 PSPMT, Xilinx Virtex-4 FPGA and Gigabit Ethernet. However, the principle of operation is the same: no hardware coincidence detection is implemented, data is acquired in list mode and transfered over an Ethernet network. The resulting new module is more suitable for full ring configurations., QC 20141106

An easy to scale up modular PET scanner was developed for imaging small animals. Energy resolution, spatial resolution and count rate performance were determined as system parameters. The configuration provided an average energy resolution of 19.6 % and the image resolution ranges was 1.5 to 2.3 mm in radial direction. The sensitivity of the miniPET was 1.08 cps/kBq as determined using a point source. In addition, results of rat brain scan performed with FDG are given to characterize imaging capability of the system. The displayed data document that the miniPET scanner supports good quality brain imaging of small animals., QC 20141202

We report on the design of a DAQ module for a small animal PET camera developed at our institutes. During the design an important guideline was to develop a system which is built up from strictly identical DAQ modules, and which has no built-in hardware limitation on the maximum number of modules. The developed DAQ module comprises of an LSO scintillator crystal block, a position sensitive PMT, analog signal conditioning circuits, a digitizer, an FPGA for digital signal processing and a communication module through which the collected data is sent to a cluster of computers for post processing and storage. Instead of implementing hardware coincidence detection between the modules we attach a precise time-stamp to each event in our design, and the coincidence is determined by the data collecting computers during the post processing. The digital CFD algorithm implemented in the FPGA gives a time resolution of 2 to 3 ns FWHM for real detector signals., QC 20141212