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Jul 27, 2018 - of human physiological optics, and the effect of varying the inference engine used to link visual representations to psy- chohysical performance.
We investigate improvements to our 3D model observer with the goal of better matching human observer performance as a function of viewing distance, effective ...
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Abstract. In reinforcement learning an agent uses online feedback from the environment in order to adaptively select an effective policy. Model free approaches ...
Picardie Jules Verne, Amiens, France (phone: 971-50-1685048; fax: 971-3-. 782-0099; e-mail: [email protected]). Hassan Noura, PhD, is Professor and ...
Abstract: This paper considers the problem of model free adaptive control (MFAC) for nonlinear systems subject to disturbances. It is shown that the robust ...
fili + (α. 2. 0 + α. 2. 1 ... + α. 2 n). 1. 2 . Let f(X) = A1X, and g(X) = BX. To facilitate the design of the nonlinear observer, perform a nonlinear state transforma-.
Electrochemical Model Based Observer Design for a. Lithium-Ion Battery. Reinhardt Klein, Nalin A. Chaturvedi, Jake Christensen, Jasim Ahmed, Rolf Findeisen, ...
I. S. Whitaker, G. F. Pratt, W. M. Rozen, S. A. Cairns, M. D. Barrett, L. Y. Hiew, M. A. .... Micromirror Device (DMD Discovery 1100, Texas Instruments Inc., Dallas, ...
Oct 14, 2015 - Supporting Information. S1 Text. PlosOneMRDSAnalysis.txt. A R script file that will replicate the results found in this manuscript. (TXT). S2 Text.
A Stereo Matching Model Observer For Stereoscopic Viewing of 3D Medical Images. Gezheng Wen1,2, Mia K. Markey3,4, Gautam S. Muralidhar5. 1Department ...
Freek J. Zijlstra, PhD, Coordinator clinical research. Department of Anaesthesiology .... speed (50 Hz) analysis and recording system. (ThermaCAM Researcher ...
This study aimed at evaluating the sensitivity, speci- ficity, reliability and repeatability of observer assess- ment of thermographic images taken from Complex.
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This single-centre retrospective longitudinal study was approved by the insti- .... non-calcified pulmonary nodules and lung parenchyma, and 150 HU between ..... Mayo-Smith, W. W., Hara, A. K., Mahesh, M., Sahani, D. V. & Pavlicek, W. How I ...
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OPEN
Received: 18 June 2018 Accepted: 14 November 2018 Published: xx xx xxxx
Task-Based Model Observer Assessment of A Partial ModelBased Iterative Reconstruction Algorithm in Thoracic Oncologic Multidetector CT David C. Rotzinger1, Damien Racine2, Catherine Beigelman-Aubry1, Khalid M. Alfudhili1, Nathalie Keller1, Pascal Monnin2, Francis R. Verdun2 & Fabio Becce1 To investigate the impact of a partial model-based iterative reconstruction (ASiR-V) on image quality in thoracic oncologic multidetector computed tomography (MDCT), using human and mathematical model observers. Twenty cancer patients examined with regular-dose thoracic-abdominal-pelvic MDCT were retrospectively included. Thoracic images reconstructed using a sharp kernel and filtered backprojection (reference) or ASiR-V (0–100%, 20% increments; follow-up) were analysed by three thoracic radiologists. Advanced quantitative physical metrics, including detectability indexes of simulated 4-mm-diameter solid non-calcified nodules and ground-glass opacities, were computed at regular and reduced doses using a custom-designed phantom. All three radiologists preferred higher ASiR-V levels (best = 80%). Increasing ASiR-V substantially decreased noise magnitude, with slight changes in noise texture. For high-contrast objects, changing the ASiR-V level had no major effect on spatial resolution; whereas for lower-contrast objects, increasing ASiR-V substantially decreased spatial resolution, more markedly at reduced dose. For both high- and lower-contrast pulmonary lesions, detectability remained excellent, regardless of ASiR-V and dose levels, and increased significantly with increasing ASiR-V levels (all p