SUNMONTUEWEDTHUFRISAT
Events for December 08, 2014
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Penalized Maximum-likelihood PET Image Reconstruction for Lesion Detection
Mon, Dec 08, 2014 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Li Yang, University of California-Davis
Talk Title: Penalized Maximum-likelihood PET Image Reconstruction for Lesion Detection
Abstract: Detecting cancerous lesions is a major clinical application in emission tomography. Statistical reconstruction methods based on the penalized maximum-likelihood (PML) principle have been developed to improve image quality. A number of metrics have been used to evaluate the quality of the reconstructed PET images, such as spatial resolution, noise variance, contrast-to-noise ratio, etc. Work has been done to optimize PML reconstruction to achieve uniform resolution and to maximize the contrast-to-noise ratio. However, these technical metrics do not necessarily reflect the performance of a clinical task. Here we focus on lesion detection and use a task-specific metric to evaluate the image quality. A multiview channelized Hotelling observer (mvCHO) is used to assess the lesion detectability in 3D images to mimic the condition where a human observer examines three orthogonal views of a 3D image for lesion detection. We derive simplified theoretical expressions that allow fast prediction of the detectability of a 3D lesion. We apply the theoretical results to guide the design of a shift-variant quadratic penalty function in PML reconstruction to maximize detectability of lesions at unknown locations in fully 3D PET. The proposed method is evaluated using computer-based Monte Carlo simulations as well as real patient data with a superimposed lesion.
Furthermore, we extend our theoretical analysis of static PET reconstruction to dynamic PET. We study both the conventional indirect reconstruction and direct reconstruction for Patlak parametric image estimation. In indirect reconstruction, Patlak parametric images are generated by reconstructing a sequence of dynamic PET images first and then performing Patlak analysis on the time activity curves (TACs) pixel-by-pixel. In direct reconstruction, Patlak parametric images are estimated directly from raw sinogram data by incorporating the Patlak model into the image reconstruction procedure. The PML reconstruction is used in both the indirect and direct reconstruction methods. Simplified expressions for evaluating the lesion detectability on Patlak parametric images have been derived and applied to the selection of the regularization parameter value to maximize the lesion detectability. Good agreements between the theoretical predictions and the Monte Carlo results are observed. The theoretical formula also shows the benefit of the direct method in dynamic PET reconstruction for lesion detection.
Biography: Li Yang received his B.S. degree in precision instrumentation from Tianjin University (China) in 2009. Currently, he is pursuing his Ph.D. degree in biomedical engineering at University of California-Davis under the supervision of Prof. Jinyi Qi. His research interests are image quality evaluation and statistical image reconstruction for emission tomography
Host: Prof. Richard Leahy
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 25
Audiences: Everyone Is Invited
Contact: Talyia Veal
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Speculative Dynamical Systems: How Technical Trading Rules Determine Price Dynamics
Mon, Dec 08, 2014 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Li-Xin Wang, Ph.D., Xian Jiaotong University, Department of Automation Science and Technology
Talk Title: Speculative Dynamical Systems: How Technical Trading Rules Determine Price Dynamics
Abstract: In this talk, I will first show how to use fuzzy systems theory to convert the following technical trading rules commonly used by stock practitioners into price dynamical equations: moving average rules, support and resistance rules, trend line rules, big buyer and big seller rules, manipulator rules, band and stop rules, and volume and relative strength rules. Then, I will analyze the price dynamical model with the moving average rules in detail, showing: (1) there exist an infinite number of price equilibriums, but all these equilibriums are unstable; (2) volatility is a deterministic function of the model parameters; (3) short-term prediction is possible with the âprediction horizonâ characterized by the Lyapunov exponent; and (4) how return correlations move from sub-diffusion to norm-diffusion and then to super-diffusion as the model parameters change. Finally, I will apply the big buyer/seller model to Hong Kong stocks and show how to detect big buyers in the market and follow them up to make money. Specifically, I will develop two trading strategies, namely Follow-the-Big-Buyer and Ride-the-Mood, and apply them to the top 20 banking and real estate stocks listed in the Hong Kong Stock Exchange for the seven-year period from July 3, 2007 to July 2, 2014; the results show that the net profits would increase 67% or 120% on average if an investor switched from the benchmark Buy-and-Hold strategy to the Follow-the-Big-Buyer or Ride-the-Mood strategies during this period, respectively. This talk is based on the paper: http://ssrn.com/abstract=2508276.
Biography: Li-Xin Wang received the Ph.D. degree from the Department of Electrical Engineering, University of Southern California, in 1992. From 1992 to 1993, he was a Postdoctoral Fellow with the Department of Electrical Engineering and Computer Science, University of California at Berkeley. From 1993 to 2007, he was on the faculty of the Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology (HKUST). In 2007, he resigned from his tenured position at HKUST to become an independent researcher and investor in the stock and real estate markets in Hong Kong and China. In Fall 2013, he returned to academic and joined the faculty of the Department of Automation Science and Technology, Xian Jiaotong University, Xian, China, after a fruitful hunting journey across the wild land of investment to achieve financial freedom. His research interests are dynamical models of asset prices, market microstructure, trading strategies, fuzzy systems, and adaptive nonlinear control. Dr. Wang received USCâs Phi Kappa Phi Student Recognition Award in 1992.
Host: Professor Jerry Mendel
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
