Paper Info
Title
Graphics Processor Unit (GPU) Accelerated Shallow Transparent Layer Detection in Optical Coherence Tomographic (OCT) Images for Real-Time Corneal Surgical Guidance.
Abstract
An image analysis algorithm is described that utilizes a Graphics Processor Unit (GPU) to detect in real-time the most shallow subsurface tissue layer present in an OCT image obtained by a prototype SDOCT corneal imaging system. The system has a scanning depth range of 6mm and can acquire 15 volumes per second at the cost of lower resolution and signal-to-noise ratio (SNR) than diagnostic OCT scanners. To the best of our knowledge, we are the first to experiment with non-median percentile filtering for simultaneous noise reduction and feature enhancement in OCT images, and we believe we are the first to implement any form of non-median percentile filtering on a GPU. The algorithm was applied to five different test images. On an average, it took similar to 0.5 milliseconds to preprocess an image with a 20th-percentile filter, and similar to 1.7 milliseconds for our second-stage algorithm to detect the faintly imaged transparent surface.
Year
DOI
Venue
2014
10.1007/978-3-319-10437-9_1
Lecture Notes in Computer Science
Keywords
Field
DocType
OCT,image-guidance,real-time,GPU,percentile filter,surface detection
Noise reduction,Computer vision,Graphical processing unit,Computer graphics (images),Computer science,Filter (signal processing),Coherence (physics),Millisecond,Artificial intelligence,Percentile
Conference
Volume
ISSN
Citations 
8678
0302-9743
0
PageRank 
References 
Authors
0.34
10
4
Name
Order
Citations
PageRank
Tejas Sudharshan Mathai131.82
J.M. Galeotti27513.90
Samantha Horvath3163.54
George D. Stetten414622.70