Scatter estimation for a digital radiographic system using convolution filtering
The use of a convolution-filtering method to estimate the scatter distribution in images acquired with a digital subtraction angiography (DSA) imaging system has been studied. Investigation of more than 175 convolution kernels applied to images of anthropomorphic head, chest, and pelvic phantoms usi...
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Published in: | Medical physics (Lancaster) Vol. 14; no. 2; p. 178 |
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Main Authors: | , |
Format: | Journal Article |
Language: | English |
Published: |
United States
01-03-1987
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Subjects: | |
Online Access: | Get more information |
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Summary: | The use of a convolution-filtering method to estimate the scatter distribution in images acquired with a digital subtraction angiography (DSA) imaging system has been studied. Investigation of more than 175 convolution kernels applied to images of anthropomorphic head, chest, and pelvic phantoms using 15-, 25-, and 36-cm fields of view (digitized onto a 512 X 512 pixel image matrix) showed that two-dimensional exponential kernels with a full width at half maximum (FWHM) of 50-150 pixels best reproduced the scatter fields within these images with a root-mean-square percentage error from 4% to 8%. A two-dimensional exponential kernal with a FWHM of 75 pixels in each dimension applied to ten different anatomic presentations and fields of view, resulted in an average root-mean-square percentage error of 6.6% for the ten cases studied. The method should be implementable using an array of small lead beam stops placed in the field of only a single mask image and the above described convolution kernel applied to both mask and postopacification images. The mask beam-stop data are used to scale both mask and postopacification convolution-filtered images. This scaled, convolution-filtered image is then subtracted from the original image to produce a largely scatter-corrected image. |
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ISSN: | 0094-2405 |
DOI: | 10.1118/1.596126 |