References  Chandler, D. M. (2013). Seven challenges in imagequalityassessment: Past, present, and future research. SRN Signal Processing, 2013, art. ID 905685.  Ponomarenko, N., Jin, L., Ieremeiev, O., Lukin, V., Egiazarian, K., Astola, J.,Vozel, B., Chehdi, K., Carli, M., Battisti, F., Kuo, C.-C. J. (2015). Image database TID2013: Peculiarities results and perspectives. Signal Processing: Image Communication, 30, 57-77.  Anbarjafari, G. (2015). An objective no-reference measure of illumination assessment. Measurement Science Review, 15(6), 319
R eferences  BOSC, E.—PEPION, R.—Le CALLET, P.—KOPPEL, M.—NDJIKI-NYA, P.—PRESSIGOUT, M.—MORIN, L. : Towards a New Quality Metric for 3-D Synthesized View Assessment, IEEE Journal on Selected Topics in Signal Processing 05 No. 07 (2011), 1332–1343.  CONZE, P. H.—ROBERT, P.—MORIN, L. : Objective View Synthesis Quality Assessment, Proc. SPIE 8288, Stereoscopic Displays and Applications XXIII (2012).  BATTISTI, F.—BOSC, E.—CARLI, M.—Le CALLET, P.—PERUGIA, S. : Objective ImageQualityAssessment of 3D Synthesized Views, Elsevier Signal Processing: Image
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The purpose of this work was to develop and validate a Monte Carlo model for a Dual Source Computed Tomography (DSCT) scanner based on the Monte Carlo N-particle radiation transport computer code (MCNP5). The geometry of the Siemens Somatom Definition CT scanner was modeled, taking into consideration the x-ray spectrum, bowtie filter, collimator, and detector system. The accuracy of the simulation from the dosimetry point of view was tested by calculating the Computed Tomography Dose Index (CTDI) values. Furthermore, typical quality assurance phantoms were modeled in order to assess the imaging aspects of the simulation. Simulated projection data were processed, using the MATLAB software, in order to reconstruct slices, using a Filtered Back Projection algorithm. CTDI, image noise, CT-number linearity, spatial and low contrast resolution were calculated using the simulated test phantoms. The results were compared using several published values including IMPACT, NIST and actual measurements. Bowtie filter shapes are in agreement with those theoretically expected. Results show that low contrast and spatial resolution are comparable with expected ones, taking into consideration the relatively limited number of events used for the simulation. The differences between simulated and nominal CT-number values were small. The present attempt to simulate a DSCT scanner could provide a powerful tool for dose assessment and support the training of clinical scientists in the imaging performance characteristics of Computed Tomography scanners.
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,O., Kittler, J., and Poh, N., :Quality controlled multi-modal fusion of biometric experts., In Progress in Pattern Recognition, Image Analysis and Applications, pages 881-890. Springer, 2007.  Kalka,N. D., Dorairaj, V.,Shah,Y. N., Schmid, N. A. and Cukic B.,: Imagequalityassessment for iris biometric., In Proceedings of the 24th Annual Meeting of the Gesellscha it Klassikation, pages 445-452. Springer, 2002.  Sandre, S-L and Stevens, M. and Mappes, J.,: The effect of predator appetite, prey warning coloration and luminance on predator foraging decisions, Behaviour
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