Effects of video frame averaging, smoothing and edge enhancement on the accuracy and precision of quantitative coronary arteriography

Abstract

Digital analysis of cine film provides numerous options for altering images by frame averaging or filtering algorithms that either smooth or enhance edges. While these may subjectively enhance image quality, there is no uniformity in their use among laboratories and effects on quantitative coronary analysis may not be ideal. To determine which processing algorithms might help or hinder quantitative coronary arteriography, cine film images of precision drilled stenotic cylinders (0.83 to 1.83 nm diameter) implanted in dog coronary arteries were analyzed with and without such algorithms. Video frame averaging of 1 to 49 frames had no effect on measures of accuracy (mean differences) but precision (standard deviation of mean differences) was improved from 0.23 to 0.17 mm (p less than 0.05) with video averaging of greater than or equal to 25 frames. Edge enhancement filtering algorithms resulted in slight deterioration of accuracy and precision and smoothing filtering algorithms caused modest improvements in these parameters; however, these changes were not significantly different from unprocessed images. Using edge enhancement filtering algorithms, accuracy was significantly worse (-0.27 mm) compared to a smoothing filter enhancement algorithm (-0.08 mm, p less than 0.001). The combination of video averaging and smoothing algorithms had no additional beneficial effects. Thus, precision of quantitative coronary analysis of cine film can be optimized by appropriate video averaging. Edge enhancement filtering algorithms should be avoided whereas smoothing filter enhancement algorithms may improve accuracy.

Advantages and limitations of two software calipers in quantitative coronary arteriography

“…On the basis of a limited phantom study we were assured that there were no statistically significant differences between the measurements performed on non-enhanced images and those on images with a medium and high degree of enhancement. Kavanaugh et al also studied the effects of video frame averaging, smoothing and edge enhancement on the accuracy and precision of the assessment of the dimensions of precision drilled stenotic cylinders (0.83 to 1.83 mm diameter) implanted in dog coronary arteries from cinefilm digitized images; in their study automated edge detection techniques were applied to digitally magnified regions of interest [15]. The precision of the measurements on cineframes acquired without frame averaging (as in our study) was found to be 0.23 mm; this is significantly larger than our worst-case findings for individual observers using a manual software caliper applied to phantom data with 100% contrast concentation.…”

Improved visualisation of choroidal neovascularisation by scanning laser ophthalmoscope using image averaging

“…[6][7][8][9][10][11][12][13][14][15] A theoretical analysis shows that the improvement of the SNR in the averaged image increases with the square root of the number of images. 13 This was confirmed in a three dimensional reconstruction of an electron microscopy tomography study 14 and in magnetic resonance imaging studies.…”

“…One of the standard technique of reducing image noise is to record a rapid series of images and average the signal over the images in the series. [6][7][8][9][10][11][12][13][14][15] Swindell and Mosleh-Shirazi have analysed the theoretical improvement that can be achieved by averaging serial images to reduce SNR 13 and found that the improvement is proportional to the square root of the number of images. However, in ophthalmic imaging applications eye motions limit the number of images that can be included.…”