Ultra-fast digital tomosynthesis reconstruction using general-purpose GPU programming for image-guided radiation therapy.
نویسندگان
چکیده
The purpose of this work is to demonstrate an ultra-fast reconstruction technique for digital tomosynthesis (DTS) imaging based on the algorithm proposed by Feldkamp, Davis, and Kress (FDK) using standard general-purpose graphics processing unit (GPGPU) programming interface. To this end, the FDK-based DTS algorithm was programmed "in-house" with C language with utilization of 1) GPU and 2) central processing unit (CPU) cards. The GPU card consisted of 480 processing cores (2 x 240 dual chip) with 1,242 MHz processing clock speed and 1,792 MB memory space. In terms of CPU hardware, we used 2.68 GHz clock speed, 12.0 GB DDR3 RAM, on a 64-bit OS. The performance of proposed algorithm was tested on twenty-five patient cases (5 lung, 5 liver, 10 prostate, and 5 head-and-neck) scanned either with a full-fan or half-fan mode on our cone-beam computed tomography (CBCT) system. For the full-fan scans, the projections from 157.5°-202.5° (45°-scan) were used to reconstruct coronal DTS slices, whereas for the half-fan scans, the projections from both 157.5°-202.5° and 337.5°-22.5° (2 x 45°-scan) were used to reconstruct larger FOV coronal DTS slices. For this study, we chose 45°-scan angle that contained ~80 projections for the full-fan and ~160 projections with 2 x 45°-scan angle for the half-fan mode, each with 1024 x 768 pixels with 32-bit precision. Absolute pixel value differences, profiles, and contrast-to-noise ratio (CNR) calculations were performed to compare and evaluate the images reconstructed using GPU- and CPU-based implementations. The time dependence on the reconstruction volume was also tested with (512 x 512) x 16, 32, 64, 128, and 256 slices. In the end, the GPU-based implementation achieved, at most, 1.3 and 2.5 seconds to complete full reconstruction of 512 x 512 x 256 volume, for the full-fan and half-fan modes, respectively. In turn, this meant that our implementation can process > 13 projections-per-second (pps) and > 18 pps for the full-fan and half-fan modes, respectively. Since commercial CBCT system nominally acquires 11 pps (with 1 gantry-revolution-per-minute), our GPU-based implementation is sufficient to handle the incoming projections data as they are acquired and reconstruct the entire volume immediately after completing the scan. In addition, on increasing the number of slices (hence volume) to be reconstructed from 16 to 256, only minimal increases in reconstruction time were observed for the GPU-based implementation where from 0.73 to 1.27 seconds and 1.42 to 2.47 seconds increase were observed for the full-fan and half-fan modes, respectively. This resulted in speed improvement of up to 87 times compared with the CPU-based implementation (for 256 slices case), with visually identical images and small pixel-value discrepancies (< 6.3%), and CNR differences (< 2.3%). With this achievement, we have shown that time allocation for DTS image reconstruction is virtually eliminated and that clinical implementation of this approach has become quite appealing. In addition, with the speed achievement, further image processing and real-time applications that was prohibited prior due to time restrictions can now be tempered with.
منابع مشابه
Ultra-Fast Image Reconstruction of Tomosynthesis Mammography Using GPU
Digital Breast Tomosynthesis (DBT) is a technology that creates three dimensional (3D) images of breast tissue. Tomosynthesis mammography detects lesions that are not detectable with other imaging systems. If image reconstruction time is in the order of seconds, we can use Tomosynthesis systems to perform Tomosynthesis-guided Interventional procedures. This research has been designed to study u...
متن کاملUltra-Fast Image Reconstruction of Tomosynthesis Mammography Using GPU
Digital Breast Tomosynthesis (DBT) is a technology that creates three dimensional (3D) images of breast tissue. Tomosynthesis mammography detects lesions that are not detectable with other imaging systems. If image reconstruction time is in the order of seconds, we can use Tomosynthesis systems to perform Tomosynthesis-guided Interventional procedures. This research has been designed to study u...
متن کاملFast Cellular Automata Implementation on Graphic Processor Unit (GPU) for Salt and Pepper Noise Removal
Noise removal operation is commonly applied as pre-processing step before subsequent image processing tasks due to the occurrence of noise during acquisition or transmission process. A common problem in imaging systems by using CMOS or CCD sensors is appearance of the salt and pepper noise. This paper presents Cellular Automata (CA) framework for noise removal of distorted image by the salt an...
متن کاملComparison of Different Reconstruction Algorithms for Decreasing the Exposure Dose during Digital Breast Tomosynthesis: A Phantom Study
We compared reconstruction algorithms [filtered back projection (FBP), maximum likelihood expectation maximization (MLEM), and the simultaneous iterative reconstruction technique (SIRT)] in terms of the radiation dose and image quality, for exploring the possibility of decreasing the radiation dose during digital breast tomosynthesis (DBT). The three algorithms were implemented using a DBT syst...
متن کاملA Comparison of Reconstruction Algorithms Regarding Exposure Dose Reductions during Digital Breast Tomosynthesis
This study compared reconstruction algorithms [filtered back projection (FBP) and simultaneous iterative reconstruction technique (SIRT)] with respect to radiation doses and image quality and suggested the possibility of decreasing the exposure dose in digital breast tomosynthesis (DBT). These two existing algorithms were implemented using a DBT system and experimentally evaluated using contras...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Technology in cancer research & treatment
دوره 10 4 شماره
صفحات -
تاریخ انتشار 2011