A compound segmentation algorithm for anterior chamber angle in OCT image

Anterior chamber (AC) angle is a useful parameter in the investigation and diagnoses of angle closure glaucoma. And Optical coherence tomography (OCT) is a noninvasive and high-resolution technique for AC angle imaging. An accurate and automatic angle measurement should be based on a precise AC angle segmentation in OCT image. However, conventional segmentation algorithms can not achieve a well result because the algorithms are not robust to the dark shadow areas and speckle noise existing in the image. A new compound segmentation algorithm is proposed in this paper. The morphological method, intensity transform, gradient image, and ratio of foreground-to-background average intensity, etc., are applied in this new algorithm to improve the accuracy of segmentation. The experiments show that the presented algorithm can achieve a satisfactory segmentation result for the AC angle in OCT images.

[1]  Joseph M. Schmitt,et al.  Optical coherence tomography (OCT): a review , 1999 .

[2]  Jing Liu,et al.  Anterior chamber angle measurement with anterior segment optical coherence tomography: a comparison between slit lamp OCT and Visante OCT. , 2008, Investigative ophthalmology & visual science.

[3]  Ying Ju,et al.  Automatic Extraction of the Anterior Chamber Contour in OCT images , 2009, 2009 Second International Symposium on Information Science and Engineering.

[4]  Iwona Gorczynska,et al.  Anterior segment imaging with Spectral OCT system using a high-speed CMOS camera. , 2009, Optics express.

[5]  Joseph A Izatt,et al.  Comparison of optical coherence tomography and ultrasound biomicroscopy for detection of narrow anterior chamber angles. , 2005, Archives of ophthalmology.

[6]  Heiko Neumann,et al.  A simple cell model with dominating opponent inhibition for robust image processing , 2004, Neural Networks.

[7]  Pierre Soille,et al.  Morphological Image Analysis: Principles and Applications , 2003 .

[8]  Luc Vincent,et al.  Morphological grayscale reconstruction in image analysis: applications and efficient algorithms , 1993, IEEE Trans. Image Process..

[9]  Paul J Foster,et al.  Detection of gonioscopically occludable angles and primary angle closure glaucoma by estimation of limbal chamber depth in Asians: modified grading scheme , 2000, The British journal of ophthalmology.

[10]  J. Fujimoto Optical coherence tomography for ultrahigh resolution in vivo imaging , 2003, Nature Biotechnology.

[11]  Christopher Kai-shun Leung,et al.  Novel approach for anterior chamber angle analysis: anterior chamber angle detection with edge measurement and identification algorithm (ACADEMIA). , 2006, Archives of ophthalmology.

[12]  Sara Rainieri,et al.  Data filtering applied to infrared thermographic measurements intended for the estimation of local heat transfer coefficient , 2002 .

[13]  J. Schuman,et al.  Optical coherence tomography. , 2000, Science.

[14]  N. Otsu A threshold selection method from gray level histograms , 1979 .