Proceeding of the 2011 IEEE Students' Technoloy Symposium 14�16 January, 2011, IIT Kharagpur ASIC Implementation of a 512-point FFT/IFFT Processor for 2D CT Image Reconstruction Algorithm Indranil Hatai\ Rakesh Biswas2, Swapna Banerjee3 Indian Institute of Technoloy Kharagpur, Department ofElectronics & Electrical Communication Engineering Kharagpur,lndia-72I302 "indranilh@cse.iitkgp.ernet.in 'rakeshbiswas2003@gmail.com 3 swapna@ece.iitkgp.ernet.in Abstract- The CT scan medical imaging requires huge amount of computations for reconstructing the images. Modiied Fast Radon Transform (MFRT) uses FFT based parallel algorithm for reconstruction of 2D/3D CT images from its sonogram data using convolution operation by concurrent ID FFT/IFFT and matrix multiplications. To achieve optimum hardware utilization with low power consumption an FFT module, based on iterative radix-2 decimation in frequency (DIF) algorithm, has been designed and implemented. The module has been designed in such way so that it can also be used for IFFT computation only by changing a single parameter. To compute the FFT, the twiddle factor has been calculated using Coordinate Rotation Digital Computer (CORDIC), by steering the data properly in the butterly structure. The synthesized frequency of FFT/IFFT module is 220 MHz and gate count is 1,040,136 using 130 nm faraday digital libraries. The power has been analyzed using prime power and the value of the power consumption is 15mW. The designed FFT/IFFT ASIC chip is very much suitable for low-area and low power biomedical applications like CT image reconstruction, Doppler wave spectrogram etc. Keywords- Modiied Fast Radon Transform (MFRT), CT images, FFTIIFFT, Coordinate Rotation Digital Computer (CODIC). I. INTRODUCTION Recent advances of CT scanner technology (1-3] have effectively yielded real-time scanning performance, making the monitoring of dynamic events such as cardiac motion possible. However, the reconstruction of images in interventional and minimally invasive surgery requires high performance computing solutions that meet operational room demands [4-8]. To achieve a higher spatial, contrast, or temporal resolution, the dimensions of input and output datasets used by the reconstruction methods are increasing rapidly [9]. The application of CT imaging is effectively limited by the performance of a single CPU computer as the reconstruction speed is concened [9]. The 'FRT' algorithm (1-2] could solve the shortcomings of the Beylkin's 'DRT' algorithm [3]; however, the'Aliasing effect' still remained as the main drawback of this method [1-3]. The antialiasing solution provided in inal form of the FRT algorithm gave rise to other subsequent diiculties such as the varying computational complexity with the worst case complexity as high as O(N 4 ). The 'zero-padding' technique effectively increases the aspect ratio r of an image and so as the maximum allowable projection angle, where Max(8)=tan' \r) (1]. However, it is practically impossible to achieve the required minimum angular coverage (±900) for complete reconstruction of an image rom its projection. This is because at the limiting condition (±90 o ) the aspect ratio r approaches to c. Therefore in spite of its several advantages the FRT is considered as an incomplete algorithm with respect to complete reconstruction. Also, the 'zero-padding' of an image signiicantly increases the computational complexity of this algorithm [1]. The Modiied-FRT (FRT) algoritm splits an image into two angular parts viz. angular region below tan- l (±r) and angular region above tan- l (±r). For a square image, the image is divided for the angular region below and above ±45°, respectively. The coordinate axes X and Y are considered to be opposite for these two images. FRT and IFRT [1] are now applied on both of these images. For a same input image the column-wise operations (e.g. FFT, IFFT) of the FRT algorithm are just changed to row-wise operations with the change in axes and vice-versa. In either of the cases angular sampling only rom 45° to +45° is considered. In this method a complete reconstruction is possible without zero padding the image. This results in a very simple reconstruction algorithm with a signiicant reduction in computational complexity of the FRT algorithm. The proposed algorithm only contains the operations like FFT/IFFT and Vector-Matrix multiplications, which can be computed either by eficient sotware programming or by using some dedicated processors to urther speed-up the computation process. However, both the methods has the same computational complexity, O(N 3 ). The block diagram of FRT processor to compute 2D radon transform at high speed is shown in Fig. 1. It consists of two parallel processing elements (PE), each constructed using FFT, vector matrix multiplier and IFFT unit. . iotm Fig. 1 Block diagram of MFRT processor TS11VLSIOl173 978-1-4244-8943-5/11/$26.00 ©2011 IEEE 220