Browsing by Author "Li, B."
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Item A Joint Unsupervised Learning and Genetic Algorithm Approach for Topology Control in Energy-Efficient Ultra-Dense Wireless Sensor Networks(Institute of Electrical and Electronics Engineers Inc.) Chang, Y.; Yuan, X.; Li, B.; Niyato, D.; Al-Dhahir, Naofal; Al-Dhahir, NaofalEnergy efficiency is a key performance metric for ultra-dense wireless sensor networks. In this letter, an unsupervised learning approach for topology control is proposed to prolong the lifetime of ultra-dense wireless sensor networks by balancing energy consumption. By encoding sensors as genes according to the network clusters, the proposed genetic-based algorithm learns an optimum chromosome to construct a close-to-optimum network topology using unsupervised learning in probability. Moreover, it schedules some of the cluster members to sleep to conserve the node energy using geographically adaptive fidelity. Simulation results demonstrate the superior performance of the proposed algorithm by improving energy efficiency in comparison with state-of-the-art algorithms at an acceptable computational complexity.Item Accelerating Chemical Exchange Saturation Transfer MRI with Parallel Blind Compressed Sensing(John Wiley and Sons Inc.) She, H.; Greer, Joshua S.; Zhang, S.; Li, B.; Keupp, J.; Madhuranthakam, A. J.; Dimitrov, I. E.; Lenkinski, R. E.; Vinogradov, E.; Greer, Joshua S.Purpose: Chemical exchange saturation transfer is a novel and promising MRI contrast method, but it can be time-consuming. Common parallel imaging methods, like SENSE, can lead to reduced quality of CEST. Here, parallel blind compressed sensing (PBCS), combining blind compressed sensing (BCS) and parallel imaging, is evaluated for the acceleration of CEST in brain and breast. Methods: The CEST data were collected in phantoms, brain (N = 3), and breast (N = 2). Retrospective Cartesian undersampling was implemented and the reconstruction results of PBCS-CEST were compared with BCS-CEST and k-t sparse-SENSE CEST. The normalized RMSE and the high-frequency error norm were used for quantitative comparison. Results: In phantom and in vivo brain experiments, the acceleration factor of R = 10 (24 k-space lines) was achieved and in breast R = 5 (30 k-space lines), without compromising the quality of the PBCS-reconstructed magnetization transfer rate asymmetry maps and Z-spectra. Parallel BCS provides better reconstruction quality when compared with BCS, k-t sparse-SENSE, and SENSE methods using the same number of samples. Parallel BCS overperforms BCS, indicating that the inclusion of coil sensitivity improves the reconstruction of the CEST data. Conclusion: The PBCS method accelerates CEST without compromising its quality. Compressed sensing in combination with parallel imaging can provide a valuable alternative to parallel imaging alone for accelerating CEST experiments.Item The Distribution of Dark and Luminous Matter in the Unique Galaxy Cluster Merger Abell 2146(Oxford University Press) King, Lindsay J.; Clowe, D. I.; Coleman, Joseph E.; Russell, H. R.; Santana, R.; White, Jacob A.; Canning, R. E. A.; Deering, Nicole J.; Fabian, A. C.; Lee, Brandyn E.; Li, B.; McNamara, B. R.; 0000 0001 2437 3571 (King, LJ); 0000-0001-8445-0444 (White, JA); King, Lindsay J.; Clowe, D. I.; Coleman, Joseph E.; Russell, H. R.; Santana, R.; White, Jacob A.; Canning, R. E. A.; Deering, Nicole J.; Fabian, A. C.; Lee, Brandyn E.; Li, B.; McNamara, B. R.Abell 2146 (z = 0.232) consists of two galaxy clusters undergoing a major merger. The system was discovered in previous work, where two large shock fronts were detected using the Chandra X-ray Observatory, consistent with a merger close to the plane of the sky, caught soon after first core passage. A weak gravitational lensing analysis of the total gravitating mass in the system, using the distorted shapes of distant galaxies seen with Advanced Camera for Surveys - Wide Field Channel on Hubble Space Telescope, is presented. The highest peak in the reconstruction of the projected mass is centred on the brightest cluster galaxy (BCG) in Abell 2146-A. The mass associated with Abell 2146-B is more extended. Bootstrapped noise mass reconstructions show the mass peak in Abell 2146-A to be consistently centred on the BCG. Previous work showed that BCG-A appears to lag behind an X-ray cool core; although the peak of the mass reconstruction is centred on the BCG, it is also consistent with the X-ray peak given the resolution of the weak lensing mass map. The best-fitting mass model with two components centred on the BCGs yields M200 = 1.1_{-0.4}^{+0.3} × 10¹⁵ and 3_{-2}^{+1} × 10¹⁴ M_⊙ for Abell 2146-A and Abell 2146-B, respectively, assuming a mass concentration parameter of c = 3.5 for each cluster. From the weak lensing analysis, Abell 2146-A is the primary halo component, and the origin of the apparent discrepancy with the X-ray analysis where Abell 2146-B is the primary halo is being assessed using simulations of the merger.Item Joint Conditional Gaussian Graphical Models with Multiple Sources of Genomic Data(2013-12-17) Chun, H.; Chen, Min; Li, B.; Zhao, H.It is challenging to identify meaningful gene networks because biological interactions are often condition-specific and confounded with external factors. It is necessary to integrate multiple sources of genomic data to facilitate network inference. For example, one can jointly model expression datasets measured from multiple tissues with molecular marker data in so-called genetical genomic studies. In this paper, we propose a joint conditional Gaussian graphical model (JCGGM) that aims for modeling biological processes based on multiple sources of data. This approach is able to integrate multiple sources of information by adopting conditional models combined with joint sparsity regularization. We apply our approach to a real dataset measuring gene expression in four tissues (kidney, liver, heart, and fat) from recombinant inbred rats. Our approach reveals that the liver tissue has the highest level of tissue-specific gene regulations among genes involved in insulin responsive facilitative sugar transporter mediated glucose transport pathway, followed by heart and fat tissues, and this finding can only be attained from our JCGGM approach.Item Multienergy Cone-Beam Computed Tomography Reconstruction with a Spatial Spectral Nonlocal Means Algorithm(Society for Industrial and Applied Mathematics Publications) Li, B.; Shen, C.; Chi, Y.; Yang, M.; Lou, Yifei; Zhou, L.; Jia, X.; 0000-0003-1973-5704 (Lou, Y); Lou, YifeiMultienergy computed tomography (CT) is an emerging medical image modality with a number of potential applications in diagnosis and therapy. However, high system cost and technical barriers obstruct its step into routine clinical practice. In this study, we propose a framework to realize multienergy cone beam CT (ME-CBCT) on the CBCT system that is widely available and has been routinely used for radiotherapy image guidance. In our method, a kVp switching technique is realized, which acquires x-ray projections with kVp levels cycling through a number of values. For this kVp-switching based ME-CBCT acquisition, x-ray projections of each energy channel are only a subset of all the acquired projections. This leads to an undersampling issue, posing challenges to the reconstruction problem. We propose a spatial spectral nonlocal means (NLM) method to reconstruct ME-CBCT, which employs image correlations along both spatial and spectral directions to suppress noisy and streak artifacts. To address the intensity scale difference at different energy channels, a histogram matching method is incorporated. Our method is different from conventionally used NLM methods in that spectral dimension is included, which helps to effectively remove streak artifacts appearing at different directions in images with different energy channels. Convergence analysis of our algorithm is provided. A comprehensive set of simulation and real experimental studies demonstrate feasibility of our ME-CBCT scheme and the capability of achieving superior image quality compared to conventional filtered backprojection-type and NLM reconstruction methods. © 2018 Society for Industrial and Applied Mathematics.Item Multienergy Element-Resolved Cone Beam CT (MEER-CBCT) Realized on a Conventional CBCT Platform(John Wiley and Sons Ltd.) Shen, C.; Li, B.; Lou, Yifei; Yang, M.; Zhou, L.; Jia, X.; 0000-0003-1973-5704 (Lou, Y); Lou, YifeiPurpose: Cone beam CT (CBCT) has been widely used in radiation therapy. However, its main application is still to acquire anatomical information for patient positioning. This study proposes a multienergy element-resolved (MEER) CBCT framework that employs energy-resolved data acquisition on a conventional CBCT platform and then simultaneously reconstructs images of x-ray attenuation coefficients, electron density relative to water (rED), and elemental composition (EC) to support advanced applications. Methods: The MEER-CBCT framework is realized on a Varian TrueBeam CBCT platform using a kVp-switching scanning scheme. A simultaneous image reconstruction and elemental decomposition model is formulated as an optimization problem. The objective function uses a least square term to enforce fidelity between x-ray attenuation coefficients and projection measurements. Spatial regularization is introduced via sparsity under a tight wavelet-frame transform. Consistency is imposed among rED, EC, and attenuation coefficients and inherently serves as a regularization term along the energy direction. The EC is further constrained by a sparse combination of ECs in a dictionary containing tissues commonly existing in humans. The optimization problem is solved by a novel alternating-direction minimization scheme. The MEER-CBCT framework was tested in a simulation study using an NCAT phantom and an experimental study using a Gammex phantom. Results: MEER-CBCT framework was successfully realized on a clinical Varian TrueBeam onboard CBCT platform with three energy channels of 80, 100, and 120 kVp. In the simulation study, the attenuation coefficient image achieved a structural similarity index of 0.98, compared to 0.61 for the image reconstructed by the conventional conjugate gradient least square (CGLS) algorithm, primarily because of reduction in artifacts. In the experimental study, the attenuation image obtained a contrast-to-noise ratio ≥60, much higher than that of CGLS results (~16) because of noise reduction. The median errors in rED and EC were 0.5% and 1.4% in the simulation study and 1.4% and 2.3% in the experimental study. Conclusion: We proposed a novel MEER-CBCT framework realized on a clinical CBCT platform. Simulation and experimental studies demonstrated its capability to simultaneously reconstruct x-ray attenuation coefficient, rED, and EC images accurately. ©2018 American Association of Physicists in Medicine