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Proceedings Paper

Brightness and contrast adjustments for different tissue densities in digital chest radiographs
Author(s): Michael F. McNitt-Gray; Ricky K. Taira; Sandra Lee Eldredge; Mahmood Razavi M.D.
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Paper Abstract

Digital chest radiographs are often too bright and/or lack contrast when viewed on a video display. This is often seen when the radiographs are taken of patients with dense lungs, have incorrect X-ray exposure technique or have inappropriate image pre-processing performed by the image acquisition system (CR system or laser scanner). This paper describes a method which can automatically provide brightness and contrast adjustments to selectively enhance either soft or dense tissues. This reduces viewer interaction and improves displayed image quality. An algorithm has been developed to analyze the gray-level histogram of a chest radiograph and determine the breakpoints that separate: (1) the region outside the patient (background), (2) the radiographically soft tissues, and (3) the radiographically dense tissues. From these breakpoint values, a series of piecewise linear look-up tables (LUTs) are generated to selectively enhance either the soft tissues or the dense tissues. This is performed by (1) varying the contrast in the patient background to achieve the desired overall brightness, (2) selectively increasing the contrast of the tissue region of interest, and (3) reducing or maintaining the contrast of the remaining region. The resulting LUTs are applied to the original image via video display.

Paper Details

Date Published: 1 June 1991
PDF: 11 pages
Proc. SPIE 1445, Medical Imaging V: Image Processing, (1 June 1991); doi: 10.1117/12.45243
Show Author Affiliations
Michael F. McNitt-Gray, Univ. of California/Los Angeles (United States)
Ricky K. Taira, Univ. of California/Los Angeles (United States)
Sandra Lee Eldredge, Univ. of California/Los Angeles (United States)
Mahmood Razavi M.D., Univ. of California/Los Angeles (United States)

Published in SPIE Proceedings Vol. 1445:
Medical Imaging V: Image Processing
Murray H. Loew, Editor(s)

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