An Optimized GPU based Filtered Backprojection method

Tomography images reconstructed from conebeam CT make it possible to observe inside of the projected object without any damage, and so it has been widely used in the industrial and medical fields. Recent advanced imaging equipment can produce high-resolution CT images. However, it takes much time to reconstruct the obtained large dataset. To reduce the time to reconstruct CT images, we propose an accelerating method using GPU (graphics processing unit). Reconstruction consists of mainly two parts, filtering and back-projection. In filtering phase, we applied 4ch image compression method and in back-projection phase, computation reduction method using depth test is applied. The experimental results show that the proposed method accelerates the speed 50 times than the CPU-based program optimized with OpenMP by utilizing the high-computing power of parallelized GPU. 핵심어: Reconstruction, GPU, Filtering, FFT, compression 본 연구는 서울시 산학연 협력사업(10888), 지식경제부 중기거점 기술개발사업(10028331-2008-23), 두뇌한국 21 지원 사업, 서울대 컴퓨터 연구소(0421-20080066) 지원으로 수행되었음. *주저자 : 서울대학교 컴퓨터공학과 석사과정 e-mail: pjh_xp@cglab.snu.ac.kr **공동저자 : 서울대학교 컴퓨터공학과 교수 e-mail: yshin@snu.ac.kr **공동저자 : 서울대학교 컴퓨터공학과 박사과정 e-mail: intellee@cglab.snu.ac.kr ***교신저자 : 서울대학교 컴퓨터공학과 박사과정 e-mail: holee@cglab.snu.ac.kr 1. 서론 삼차원 재구성(Reconstruction)이란, 물체를 중심으로 일정 각도 간격으로 회전하며 얻은 투영 영상으로부터, 공간적 해석이 가능한 단층영상들을 생성하는 것을 HCI2009 학술대회