Principles of computerized tomographic imaging
Principles of computerized tomographic imaging
O(N2log2N) filtered backprojection reconstruction algorithm for tomography
IEEE Transactions on Image Processing
Parallel-Beam Backprojection: An FPGA Implementation Optimized for Medical Imaging
Journal of VLSI Signal Processing Systems
Parallel-beam backprojection: an FPGA implementation optimized for medical imaging
Journal of VLSI Signal Processing Systems
Hardware/software 2D-3D backprojection on a SoPC platform
Proceedings of the 2006 ACM symposium on Applied computing
An overview of reconfigurable hardware in embedded systems
EURASIP Journal on Embedded Systems
Parallel backprojection: a case study in high-performance reconfigurable computing
EURASIP Journal on Embedded Systems - FPGA supercomputing platforms, architectures, and techniques for accelerating computationally complex algorithms
GPU-based cone beam computed tomography
Computer Methods and Programs in Biomedicine
Evaluation of the reconfiguration of the data acquisition system for 3D USCT
International Journal of Reconfigurable Computing - Special issue on selected papers from the international workshop on reconfigurable communication-centric systems on chips (ReCoSoC' 2010)
A coarse-grained stream architecture for cryo-electron microscopy images 3D reconstruction
Proceedings of the ACM/SIGDA international symposium on Field Programmable Gate Arrays
Wheelchairs Embedded Control System Design for Secure Navigation with RF Signal Triangulation
Journal of Information Technology Research
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Medical image processing in general and computerized tomography (CT) in particular can benefit greatly from hardware acceleration. This application domain is marked by computationally intensive algorithms requiring the rapid processing of large amounts of data. To date, reconfigurable hardware has not been applied to this important area. For efficient implementation and maximum speedup, fixed-point implementations are required. The associated quantization errors must be carefully balanced against the requirements of the medical community. Specifically, care must be taken so that very little error is introduced compared to floating-point implementations and the visual quality of the images is not compromised. In this paper, we present an FPGA implementation of the parallel-beam backprojection algorithm used in CT for which all of these requirements are met. We explore a number of quantization issues arising in backprojection and concentrate on minimizing error while maximizing efficiency. Our implementation shows significant speedup over software versions of the same algorithm, and is more flexible than an ASIC implementation. Our FPGA implementation can easily be adapted to both medical sensors with different dynamic ranges as well as tomographic scanners employed in a wider range of application areas including nondestructive evaluation and baggage inspection in airport terminals.