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Proceedings Paper

Medical Image Communication Using Halftone Algorithms
Author(s): Robert B. Goldstein; Eli Peli; Karl Wooledge
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Paper Abstract

Physicians frequently need to see retinal, biopsy, and other images, produced originally by medical diagnostic equipment and then processed by computers. At present this is done using either time-consuming photography or expensive video equipment. We have used digital halftoning as a method for fast communication of images both on print and on computer terminal screens. This method quickly produces a good-quality halftone rendition of a grey-scale image. These images are suitable for display and printout on inexpensive devices that normally do not have grey-scale capability. The algorithm is based on a previously published error-propagation technique. We improved the algorithm by including a factor that accounts for the difference in size between light and dark points on various devices. The algorithm is extended to devices that have two bitplanes (VT240), and the execution and transmission times are reduced. At Tufts-New England Medical Center in Boston, this program has been used in processing and reporting the results of muscle and nerve biopsies. At the Eye Research Institute in Boston, it has been used to report the results of retinal visual field mapping. This technique has a wide range of applications. It allows "image processing" to be done on computers that have no traditional image-processing hardware. It allows several users to operate simultaneously on time-shared systems that have only a single image-processor. Images are displayed on 1 or 2 bitplane devices (LA50 printers or VT240 terminals). It allows image transmission over long distances --replacing video communication equipment with RS232 cables and modems.

Paper Details

Date Published: 13 October 1987
PDF: 6 pages
Proc. SPIE 0845, Visual Communications and Image Processing II, (13 October 1987); doi: 10.1117/12.976533
Show Author Affiliations
Robert B. Goldstein, Harvard Medical School (United States)
Eli Peli, Harvard Medical School (United States)
Karl Wooledge, Tufts-New England Medical Center (United States)

Published in SPIE Proceedings Vol. 0845:
Visual Communications and Image Processing II
T. Russell Hsing, Editor(s)

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