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Proceedings Paper

Image-display optimization using clinical history
Author(s): Calvin F. Nodine; Inna Brikman; Harold L. Kundel; A. Douglas; Sridhar B. Seshadri; Ronald L. Arenson
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Paper Abstract

Modern imaging technology places new perceptual and cognitive demands on skilled interpreters of medical images. As a result, medical users sometimes perceive new display systems as clumsy and unfriendly because they are required to interactively manipulate images in ways that are foreign to them. The primary goal of this research is to transfer some of the burden of image manipulation from the observer to the computer. This will be accomplished by using clinical history prompts to set gray-scale imaging parameters that are most likely to enhance relevant diagnostic information called for by the prompt. The image processing is done in a series of invisible, off-line ''steps'' which normalize the gray-scale range, and display an image that has been tuned by an optimum gray-scale Look Up Table (LUT) derived from clinical-history data. The criteria that we have emphasized in designing the workstation are that it (a) is user friendly, (b) incorporates human-perception principles in the display interface, and (c) utilizes gray-scale transfer functions that improve contrast resolution of prompt-targeted diagnostic information. We will report on an experimental display workstation that links clinical-history prompts to an optimized gray-scale LUT. The clinical histories provide the basis for generating rules that call up a gray-scale transfer function designed to optimally display targeted diagnostic information in the medical image. From a perceptual point of view, a workstation that can display optimized images would mean that the initial transformed image not only matches the diagnostic disease category, but also the observer''s perceptual hypothesis so that a global diagnostic interpretation is possible before any fine- tuning of window and level settings. Because the initial perceptual encounter with the image fits observer expectancies, global pattern recognition should be facilitated.

Paper Details

Date Published: 1 May 1991
PDF: 7 pages
Proc. SPIE 1444, Medical Imaging V: Image Capture, Formatting, and Display, (1 May 1991); doi: 10.1117/12.45155
Show Author Affiliations
Calvin F. Nodine, Univ. of Pennsylvania (United States)
Inna Brikman, Univ. of Pennsylvania (United States)
Harold L. Kundel, Univ. of Pennsylvania (United States)
A. Douglas, Univ. of Pennsylvania (United States)
Sridhar B. Seshadri, Univ. of Pennsylvania (United States)
Ronald L. Arenson, Univ. of Pennsylvania Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 1444:
Medical Imaging V: Image Capture, Formatting, and Display
Yongmin Kim, Editor(s)

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