Effects of Varying Filter Kernel Sizes on the Image Quality of Interstitial Lung Diseases

Spatial unsharp-mask processing and its variants are commonly used in x-ray radiography to enhance image contrast. We investigated the effect of three unsharp-masking filter kernels of different sizes on the detection of an advanced guidewire tip in simulated x-ray fluoroscopy image sequences. To isolate the effect of visual temporal processing, we repeated the experiments on single images. Filter gains were selected so that all three kernels increased the contrast of a 0.018-in. (0.457-mm) guidewire by a factor of 2 but had different effects on image noise and signal profiles. There was no statistically significant effect of unsharp masking on human-observer performance in single images. However, all three kernels significantly improved average performance in image sequences, and the guidewire contrast required for detection was reduced by 32%-40%. A prewhitening channelized observer model predicted the disparity between sequences and single images and fitted measurements at different kernel sizes well. A nonprewhitening observer model did not. We conclude that unsharp masking is a simple and effective method of improving guidewire visualization in fluoroscopically guided interventional procedures and that quantitative image quality studies are essential for evaluation of image-processing techniques in sequences such as x-ray fluoroscopy.

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Effects of Varying Filter Kernel Sizes on the Image Quality of Interstitial Lung Diseases

Abstract: Whenever optimized postprocessing is involved, storage phosphor radiography is equal to a modern screen-film system and can be substituted for the latter without any loss of image quality; this is especially valid for the imaging of interstitial infiltrates of the lung.

Cited by 2 publications

References 25 publications

Selection of Appropriate Computed Tomographic Image Reconstruction Algorithms for a Quantitative Multicenter Trial of Diffuse Lung Disease

Selection of Appropriate Computed Tomographic Image Reconstruction Algorithms for a Quantitative Multicenter Trial of Diffuse Lung Disease

Quantitative assessment of image quality enhancement due to unsharp-mask processing in x-ray fluoroscopy

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