Paper
27 June 1988 Methodology For Evaluating Computer Enhancement Techniques For Processing Digital Images
Kelly Rehm, George W. Seeley, William J. Dallas, Theron W. Ovitt, M. Paul Capp, J. D. Newell
Author Affiliations +
Abstract
An experimental design has been devised and tested for evaluating computerized contrast enhancement techniques designed for the task of improving lung nodule detection accuracy in digital chest radiographs. Under this design, a global contrast enhancement technique has been tested which provided images resulting in improved detection of simulated chest nodules. The work was conducted using images from a Toshiba Computed Radiography System (TCR-201). The images used were made using a 3M chest phantom with simulated nodules of four diameters and two thicknesses. Each image that contained a nodule only had one, and it was in one of only four possible locations. A phantom with location and background information provided to the observer was used to eliminate confounding factors affecting the evaluation of detectability. A relatively simple histogram modification algorithm processed the data, and the resulting images were written to film by the TCR system. A psychophysical study was conducted to compare detection ability with the enhanced images versus standard TCR processed images. In a film-to-film comparison of 48 cases (32 with nodules), when viewing the enhanced images, two out of three observers achieved a distinct improvement in true/positive responses over the ordinary TCR images with no increase in false/positive responses.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kelly Rehm, George W. Seeley, William J. Dallas, Theron W. Ovitt, M. Paul Capp, and J. D. Newell "Methodology For Evaluating Computer Enhancement Techniques For Processing Digital Images", Proc. SPIE 0914, Medical Imaging II, (27 June 1988); https://doi.org/10.1117/12.968704
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Cited by 1 scholarly publication.
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KEYWORDS
Image processing

Radiology

Image enhancement

Chest

Lung

Detection and tracking algorithms

Medical imaging

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