System design and image processing algorithms for frequency domain optical coherence tomography in the coronary arteries

2010 ◽  
Author(s):  
Desmond C. Adler ◽  
Chenyang Xu ◽  
Christopher Petersen ◽  
Joseph M. Schmitt
Keyword(s):  
Image Processing ◽  
Optical Coherence Tomography ◽  
System Design ◽  
Frequency Domain ◽  
Coronary Arteries ◽  
Optical Coherence ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Image synthesis methodology for algorithm testing and vision system design

2002 ◽  
Vol 216 (5) ◽  
pp. 669-682 ◽  
Author(s):  
J M Parker ◽  
K-M Lee
Keyword(s):  
Image Processing ◽  
System Design ◽  
Vision System ◽  
Image Synthesis ◽  
Image Understanding ◽  
Design Parameters ◽  
Wide Range ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Synthesis Methodology

Although it is well-recognized and widely accepted that vision adds considerable flexibility, and it has also been shown that numerical simulation can aid in image understanding and vision system design (significantly reducing the engineering time to design and implement such systems), the utilization of image synthesis as an aid in algorithm and system design still remains a largely underexplored area. In machine vision applications, accuracy of the image generally outweighs image appearance. Unfortunately, the focus of most commercially available simulation methods is on photorealistic image synthesis; this is insufficient to design vision systems or evaluate and compare image-processing algorithms for part-presentation tasks: physically accurate, rather than photo-realistic, synthesis methods are necessary to sufficiently simulate captured image grey-scale values. This paper presents a methodology to generate physically accurate synthetic images efficiently in order to provide an accurate, flexible and practical means of evaluating the performance of image-processing algorithms for numerous hardware/software configuration combinations and a wide range of parts. While the synthesis methodology cannot fully compensate for the real environment, it can be used efficiently to study the effects of vision system design parameters on image accuracy. This provides an insight into the efficacy of the design and the ability of suggested image-processing algorithms to perform adequately for specific applications; furthermore, it may provide a means for correcting apparent errors in image-processing results.

Abstract 367: Measurement of Lumen Dimensions in Non-stented and Stented Coronary Arteries: A Meta-analysis of Frequency Domain Optical Coherence Tomography versus Intravascular Ultrasound

2015 ◽  
Vol 8 (suppl_2) ◽  
Author(s):  
Samit Bhatheja ◽  
Hemang Panchal ◽  
Neil Barry ◽  
Zia Rahman ◽  
Timir Paul
Keyword(s):  
Optical Coherence Tomography ◽  
Frequency Domain ◽  
Intravascular Ultrasound ◽  
Coronary Arteries ◽  
Meta Analysis ◽  
Lumen Diameter ◽  
Optical Coherence ◽  
Lumen Area ◽  
Minimum Lumen Diameter ◽  
Significant Difference

Background: Intraluminal coronary morphology is traditionally evaluated by Intravascular Ultrasound (IVUS). Frequency Domain Optical Coherence Tomography (FD-OCT) is a novel method for evaluation of coronary lumen dimensions. Current literature has paucity of data with limited sample size comparing FD-OCT to IVUS. The objective of this meta-analysis is to compare the FD-OCT versus IVUS in assessment of lumen dimensions in non-stented and stented coronary arteries. Methods: PubMed and the Cochrane Center Register of Controlled Trials were searched through January 2015. Seven studies (n=169 vessels) comparing FD-OCT versus IVUS procedures in assessing lumen dimensions in non-stented and stented coronary arteries were included. Outcomes were minimum lumen area, minimum lumen diameter and maximum lumen diameter. The mean difference (MD) with 95% confidence interval (CI) was computed and p<0.05 was considered as a level of significance. Results: FD-OCT measured significantly smaller minimum lumen area and maximum lumen diameter compared to IVUS in non-stented vessels (MD: -0.86 mm 2 , CI: -1.18 to -0.55, p<0.00001 and MD: -0.21 mm, CI: -0.35 to -0.06, p=0.006, respectively). Minimum lumen diameter was not significantly different between two groups in non-stented coronary arteries (p=0.21). In stented vessels, no significant difference was found in measurement of minimum lumen area (p=0.34) and minimum lumen diameter (p=0.41) between FD-OCT and IVUS. Conclusion: The results of this study suggest that FD-OCT maybe a better modality to evaluate the severity of stenosis in non-stented coronary arteries. FD-OCT is comparable to IVUS in measuring lumen dimensions in stented vessels.

scholarly journals Benchmarking Image Processing Algorithms for Unmanned Aerial System-Assisted Crack Detection in Concrete Structures

2019 ◽  
Vol 4 (2) ◽  
pp. 19 ◽  
Author(s):  
Dorafshan ◽  
Thomas ◽  
Maguire
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Frequency Domain ◽  
Crack Width ◽  
Crack Detection ◽  
Spatial Domain ◽  
Gaussian Filter ◽  
Laplacian Of Gaussian Filter ◽  
Image Processing Algorithms ◽  
Processing Algorithms

This paper summarizes the results of traditional image processing algorithms for detection of defects in concrete using images taken by Unmanned Aerial Systems (UASs). Such algorithms are useful for improving the accuracy of crack detection during autonomous inspection of bridges and other structures, and they have yet to be compared and evaluated on a dataset of concrete images taken by UAS. The authors created a generic image processing algorithm for crack detection, which included the major steps of filter design, edge detection, image enhancement, and segmentation, designed to uniformly compare different edge detectors. Edge detection was carried out by six filters in the spatial (Roberts, Prewitt, Sobel, and Laplacian of Gaussian) and frequency (Butterworth and Gaussian) domains. These algorithms were applied to fifty images each of defected and sound concrete. Performances of the six filters were compared in terms of accuracy, precision, minimum detectable crack width, computational time, and noise-to-signal ratio. In general, frequency domain techniques were slower than spatial domain methods because of the computational intensity of the Fourier and inverse Fourier transformations used to move between spatial and frequency domains. Frequency domain methods also produced noisier images than spatial domain methods. Crack detection in the spatial domain using the Laplacian of Gaussian filter proved to be the fastest, most accurate, and most precise method, and it resulted in the finest detectable crack width. The Laplacian of Gaussian filter in spatial domain is recommended for future applications of real-time crack detection using UAS.

Sign in / Sign up

Export Citation Format

Share Document