DocumentCode :
501720
Title :
Automated Thickness Measurements of Pearl from Optical Coherence Tomography Images
Author :
Lei, Ming ; Sun, Yankui ; Wang, Daoshun ; Li, Peng
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Volume :
1
fYear :
2009
fDate :
12-14 Aug. 2009
Firstpage :
247
Lastpage :
251
Abstract :
In this paper, we explored the automatic thickness measurements of pearl from optical coherence tomography (OCT) images. We used a two stage scheme to extract the upper and lower boundaries of nacre respectively, and computed the thickness of nacre based on the extracted upper and lower boundaries. At the first stage, we employed edge detection method to extract the upper boundary. At the following stage, we used pixel classification method to detect the lower boundary. In both stages, boundary refinement and fitting were conducted. The proposed approach is evaluated using pearl optical coherence tomography images, and achieved high segmentation accuracy of 93.56% and relative measurement error of 1.69%. Experimental results demonstrate the effectiveness and robustness of our method.
Keywords :
edge detection; image classification; medical image processing; optical tomography; thickness measurement; automated thickness measurements; boundary refinement; edge detection method; pearl optical coherence tomography images; pixel classification method; Biomedical measurements; Biomedical optical imaging; High-resolution imaging; Image edge detection; Nonlinear optics; Optical imaging; Optical scattering; Thickness measurement; Tomography; Ultrasonic imaging; Support vector machine; boundary fitting; nonlinear complex diffusion; optical coherence tomography; pearl;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hybrid Intelligent Systems, 2009. HIS '09. Ninth International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-0-7695-3745-0
Type :
conf
DOI :
10.1109/HIS.2009.56
Filename :
5254320
Link To Document :
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