Contrast improvements in digital radiography using a scatter-reduction processing algorithm

Kent M. Ogden; Charles R. Wilson; Robert W. Cox

doi:10.1117/12.467059

9 May 2002 Contrast improvements in digital radiography using a scatter-reduction processing algorithm

Kent M. Ogden, Charles R. Wilson, Robert W. Cox

Proceedings Volume 4684, Medical Imaging 2002: Image Processing; (2002) https://doi.org/10.1117/12.467059
Event: Medical Imaging 2002, 2002, San Diego, California, United States

Abstract

An expectation maximization (EM) algorithm has been developed based on a model of radiographic imaging that accounts for scatter radiation and resolution degradation. Digital radiographs of a chest phantom were acquired, and the amount of scatter in several regions was computed using the known radiographic exposure and the known material properties. Contrast and noise were measured in a step wedge in the phantom. The phantom images were processed by the EM algorithm for up to 8 iterations, and the image intensity and noise values were measured at each iteration step. These values were used to compute the scatter reduction properties of the algorithm and its effect on the contrast-to-noise ratio. The algorithm removed over 90% of the scattered radiation in the image. Image noise values were reduced an average of 50% in the first iteration, but then increased to values equal or above unprocessed images. The contrast-to- noise ratio was initially increased substantially, but gradually decreased as further iterations caused the image noise to increase. With proper selection of processing parameters, this algorithm could provide considerable qualitative enhancement of clinical images with a single iteration as well as numerically accurate scatter reduction.

Citation Download Citation

Kent M. Ogden, Charles R. Wilson, and Robert W. Cox "Contrast improvements in digital radiography using a scatter-reduction processing algorithm", Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); https://doi.org/10.1117/12.467059

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