A CT metal artifact reduction algorithm based on sinogram surgery
Jeon, Soomin
;
Lee, Chang-Ock
초록
BACKGROUND: Streak artifacts in computed tomography (CT) images caused by metallic objects limit the wider use of CT imaging technologies. There have been various attempts to improve CT images containing streak artifacts; however, most of them generate additional artifacts or do not completely eradicate existing artifacts. OBJECTIVE: In this paper, we propose a novel algorithm which reduces streak artifacts in CT images. METHODS: Using CT numbers reconstructed from a given sinogram, we extract the metal partM and the surrounding area C with similar CT numbers. By filling in the area C. M with the evaluated average CT number of C, we obtain a modified CT image. Using forward projection of the modified CT image, we generate a sinogram containing information about the anatomical structure. We undertake sinogram surgery to remove the metallic effects from the sinogram, after which we repeat the procedure. RESULTS: We perform numerical experiments using various simulated phantoms and patient images. For a quantitative analysis, we use the relative l(infinity) error and the relative l(2) error. In simulated phantom experiments, all l(infinity) errors and l(2) errors approach 10% and1% of the initial errors, respectively. Moreover, for the patient image simulations, all l(infinity) errors are decreased by a factor of 20 while the l(2) errors are decreased less than 5%. We observe that the proposed algorithm effectively reduces the metal artifacts. CONCLUSIONS: In this paper, we propose a metal artifact reduction algorithm based on sinogram surgery to reduce metal artifacts without additional artifacts. We also provide empirical convergence of our algorithm.
서지사항
JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY, v.26, no.3, pp.413 - 434, 2018-06
In this paper, we introduce a promising iterative interference alignment (IA) strategy for multiple-input multiple-output (MIMO) multi-cell downlink networks, which utilizes the channel reciprocity between uplink/downlink channels. We intelligently combine iterative beamforming and downlink IA issues to design an iterative multiuser MIMO IA algorithm. The proposed scheme uses two cascaded beamforming matrices to construct a precoder at each base station (BS), which not only efficiently reduce the effect of inter-cell interference from other-cell BSs, referred to as leakage of interference, but also perfectly eliminate intra-cell interference among spatial streams in the same cell. The transmit and receive beamforming matrices are iteratively updated until convergence. Numerical results indicate that our IA scheme exhibits higher sum-rates than those of the conventional iterative IA schemes. Note that our iterative IA scheme operates with local channel state information, no time/frequency expansion, and even relatively a small number of mobile stations (MSs), unlike opportunistic IA which requires a great number of MSs.
서지사항
IEICE TRANSACTIONS ON COMMUNICATIONS, v.E98B, no.5, pp.834 - 841, 2015-05
Sparse-view proton computed tomography using modulated proton beams
Lee, Jiseoc
;
Kim, Changhwan
;
Min, Byungjun
;
Kwak, Jungwon
;
Park, Seyjoon
;
Lee, Se Byeong
;
Park, Sungyong
;
Cho, Seungryong
초록
Purpose: Proton imaging that uses a modulated proton beam and an intensity detector allows a relatively fast image acquisition compared to the imaging approach based on a trajectory tracking detector. In addition, it requires a relatively simple implementation in a conventional proton therapy equipment. The model of geometric straight ray assumed in conventional computed tomography (CT) image reconstruction is however challenged by multiple-Coulomb scattering and energy straggling in the proton imaging. Radiation dose to the patient is another important issue that has to be taken care of for practical applications. In this work, the authors have investigated iterative image reconstructions after a deconvolution of the sparsely view-sampled data to address these issues in proton CT. Methods: Proton projection images were acquired using the modulated proton beams and the EBT2 film as an intensity detector. Four electron-density cylinders representing normal soft tissues and bone were used as imaged object and scanned at 40 views that are equally separated over 360 degrees. Digitized film images were converted to water-equivalent thickness by use of an empirically derived conversion curve. For improving the image quality, a deconvolution-based image deblurring with an empirically acquired point spread function was employed. They have implemented iterative image reconstruction algorithms such as adaptive steepest descent-projection onto convex sets (ASD-POCS), superiorization method-projection onto convex sets (SM-POCS), superiorization method-expectation maximization (SM-EM), and expectation maximization-total variation minimization (EM-TV). Performance of the four image reconstruction algorithms was analyzed and compared quantitatively via contrast-to- noise ratio (CNR) and root-mean-square-error (RMSE). Results: Objects of higher electron density have been reconstructed more accurately than those of lower density objects. The bone, for example, has been reconstructed within 1% error. EM-based algorithms produced an increased image noise and RMSE as the iteration reaches about 20, while the POCS-based algorithms showed a monotonic convergence with iterations. The ASD-POCS algorithm outperformed the others in terms of CNR, RMSE, and the accuracy of the reconstructed relative stopping power in the region of lung and soft tissues. Conclusions: The four iterative algorithms, i.e., ASD-POCS, SM-POCS, SM-EM, and EM-TV, have been developed and applied for proton CT image reconstruction. Although it still seems that the images need to be improved for practical applications to the treatment planning, proton CT imaging by use of the modulated beams in sparse-view sampling has demonstrated its feasibility.
서지사항
MEDICAL PHYSICS, v.42, no.2, pp.1129 - 1137, 2015-02
Dual Sampling Rate Observer for Motor Position Estimation Using Linear Hall Sensors and Iterative Algorithm
Kim, Jonghwa
;
Kim, Min Hyun
;
Cho, Kwanghyun
;
Choi, Seibum B
초록
This study suggests a position estimator using linear hall effect sensors and iterative algorithm. Compared to other typical position sensors such as encoders and resolvers, hall effect sensors have several advantages. (e.g., insensitivity to both external disturbances and environmental contaminations, and having a scaleless property). Furthermore, linear hall sensors provide more detailed information on the motor position (i.e., finer resolution) than that of square wave hall sensors. Using those characteristics, a position estimator with linear hall sensors is proposed. Considering the sinusoidal property of the magnetic flux distribution along the position of the motor system, an iterative algorithm with dual sampling rates is applied. The effectiveness of the suggested method was validated with a simulation.
학술대회명
The 19th International Conference on Electrical Machines and Systems (ICEMS2016)
Combining tactile sensing and vision for rapid haptic mapping
Bhattacharjee, Tapomayukh
;
Shenoi, Ashwin A.
;
Park, Daehyung
;
Rehg, James M.
;
Kemp, Charles C.
초록
We consider the problem of enabling a robot to efficiently obtain a dense haptic map of its visible surroundings using the complementary properties of vision and tactile sensing. Our approach assumes that visible surfaces that look similar to one another are likely to have similar haptic properties. We present an iterative algorithm that enables a robot to infer dense haptic labels across visible surfaces when given a color-plus-depth (RGB-D) image along with a sequence of sparse haptic labels representative of what could be obtained via tactile sensing. Our method uses a color-based similarity measure and connected components on color and depth data. We evaluated our method using several publicly available RGBD image datasets with indoor cluttered scenes pertinent to robot manipulation. We analyzed the effects of algorithm parameters and environment variation, specifically the level of clutter and the type of setting, like a shelf, table top, or sink area. In these trials, the visible surface for each object consisted of an average of 8602 pixels, and we provided the algorithm with a sequence of haptically-labeled pixels up to a maximum of 40 times the number of objects in the image. On average, our algorithm correctly assigned haptic labels to 76.02% of all of the object pixels in the image given this full sequence of labels. We also performed experiments with the humanoid robot DARCI reaching in a cluttered foliage environment while using our algorithm to create a haptic map. Doing so enabled the robot to reach goal locations using a single plan after a single greedy reach, while our previous tactile-only mapping method required 5 or more plans to reach each goal.
학술대회명
IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015