Computer Science – Performance
Scientific paper
Nov 2000
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2000spie.4123..285r&link_type=abstract
Proc. SPIE Vol. 4123, p. 285-294, Image Reconstruction from Incomplete Data, Michael A. Fiddy; Rick P. Millane; Eds.
Computer Science
Performance
Scientific paper
During the last few years, OCT has demonstrated considerable promise as a method of high-resolution intravascular imaging. The goal of this study was to apply and to test the applicability of the rotating kernel transformation (RKT) technique to the speckle reduction and enhancement of OCT images. The technique is locally adaptive. It is based on sequential application of directional masks and selection of the maximum of all outputs. This method enhances the image features by emphasizing thin edges while suppressing a noisy background. Qualitatively, the RKT algorithm provides noticeable improvement over the original image. All processed images are smoother and have better-defined borders of media, intima, and plaque. The quantitative evaluation of RKT performance showed that in terms of average contrast-to-noise ratio, there is a significant improvement in image quality between original and enhanced images. The RKT image enhancement technique shows great promise in improving OCT images for superior boundary identification.
Brezinski Mark E.
Rogowska Jadwiga
No associations
LandOfFree
Evaluation of rotational kernel transformation technique for enhancement of coronary optical coherence tomography images does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Evaluation of rotational kernel transformation technique for enhancement of coronary optical coherence tomography images, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Evaluation of rotational kernel transformation technique for enhancement of coronary optical coherence tomography images will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1116209