PubMed · 11905694
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G Kenyon. 2000. New virtual computer on trial.. https://doi.org/10.1016/s1470-2045(00)00095-4
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A fast method for fitting model electron densities into EM reconstructions is presented. The methodology was inspired by the molecular-replacement technique, adapted to take into account phase information and the symmetry imposed during the EM reconstruction. Calculations are performed in reciprocal space, which enables the selection of large volumes of the EM maps, thus avoiding the bias introduced when defining the boundaries of the target density.
In this paper we generalize the approach of Ahonen et al (1993 IEEE Trans. Biomed. Eng. 40 859-69) to two-dimensional non-uniform sampling. The focus is on two main topics: (1) searching for the optimal sensor configuration on a planar measurement surface; and (2) reconstructing the magnetic field (a continuous function) from a discrete set of data points recorded with a finite number of sensors. A reconstruction formula for Bz is derived in the framework of the multidimensional Papoulis generalized sampling expansion (Papoulis A 1977 IEEE Trans. Circuits Syst. 24 652-4, Cheung K F 1993 Advanced Topics in Shannon Sampling and Interpolation Theory (New York: Springer) pp 85-119) in a particular case. Application of these considerations to the design of biomagnetic sensor arrays is also discussed.
This article presents a computer correction technique for radiographic digital images based on digitization process inaccuracy in pixel gray levels relative to the respective image optical densities. The technique consists of determining the digitizer characteristic curve by digitizing a step-wedge radiographic image with known optical densities. Calibration is done by determining the mathematical function that automatically adjusts the pixel gray levels to the expected values according to the manufacturer. Two laser film digitizers were investigated for which discrepancies between measured and expected pixel values were reported. For these cases, the proposed algorithm automatically adjusted the pixel gray levels of the digitized images. Using this method, the digital images show more accurate values of gray levels compared to the original radiographic image. In addition, it allows the development of uniform images databases.