Browse > Article

Sclera Segmentation for the Measurement of Conjunctival Injection  

Bae, Jang-Pyo (서울대학교 협동과정 바이오엔지지어링)
Kim, Kwang-Gi (국립암센터 의공학연구과)
Jeong, Chang-Bu (국립암센터 의공학연구과)
Yang, Hee-Kyung (분당서울대학교병원 안과)
Hwang, Jeong-Min (분당서울대학교병원 안과)
Publication Information
Abstract
Conjunctival injection is the initial symptom of various eye diseases such as conjunctivitis, keratitis, or uveitis. The quantification of conjunctival injection may help the diagnosis and follow-up evaluation of various eye diseases. The size of the sclera is an important factor for the quantification of conjunctival injection. However, previous manual segmentation is time-consuming.Automatic segmentation is needed to extract the objective region of interest. This paper proposed a method based on the level set algorithm to segment the sclera from an anterior eye image. The initial model of the level set algorithm is calculated using the Lab color space, k-means algorithm and the geometric information. The level set algorithm was applied to the images in which the valley between the eyeball and skin was enhanced using the hessian analysis. This algorithm was tested with 52 images of the anterior eye segment. Results showed that the proposed method performs better than those with the level set algorithm using an arbitrary circle, or the region growing algorithm with color information. The proposed method for the segmentation of sclera may become an important component for the objective measurement of the conjunctival injection.
Keywords
Sclera Segmentation; Conjunctival Injection; Level Set;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Z. Zhang, W. V. Stoecker, and R. H. Moss, "Border Detection on Digitized Skin Tumor Images," Ieee T Med Imaging, Vol.19, Issue 11, pp. 1128-1143, Nov. 2000.   DOI   ScienceOn
2 L. Sorbara, T. Simpson, S. Duench, M. Schulze, and D. Fonn, "Comparison of an objective method of measuring bulbar redness to the use of traditional grading scales," Cant Lens Anterior Eye, Vol.30, pp 53-59, 2007.   DOI   ScienceOn
3 J. S. Wolffsohn, "Incremental nature of anterior eye grading scales determined by objective image analysis," Br J Ophthalmol, Vol. 88, pp.1434-1438, 2004.   DOI   ScienceOn
4 강호철, 김광기, 오휘빈, 황정민, "전안부 영상에서의 동공 및 홍채 영상 분할 연구," 대한의료정보학회지, 제15권, 제2호, pp.227-234, 2009.
5 V. Vezhnevets and A Degtiareva, "Robust and Accurate Eye Contour Extraction," Proc. Graphicon-2003, pp.81-84, 2003.
6 Z. Hammal and A Caplier, and eyebrows parametric models for automatic segmentation," Proc. IEEE Southwest Symposium on Image Analysis and Interpretation, USA, pp. 138-141, March 2004.
7 J. S. Suri, L. Kecheng, S. Singh, S. N. Laxminarayan, Z.xiaolan, and L. Reden, "Shape recovery algorithms using level sets in 2-D/3 D medical imagery: a state-of-the-art review," Ieee T Inf Technol B, Vol.6, Issue.1, pp.8-28, March 2002.   DOI   ScienceOn
8 H.-G. Geovanni, E. S.-Y. Raul, A.-R. Victor, and E. C.-T. Fernando, "Natural Image Segmentation Using the CIELab Space," 2009 International Conference on Electrical, Communications, and Computers, pp.107-110, 2009.
9 J. B. MacQueen, "Some Methods for classification and Analysis of Multivariate Observations," Proceedings of the Fifth Berkeley Symposium on Mathematics, Statistics, and Probability, Berkeley, U. California Press, pp. 281-297, 1967.
10 C. Li, C. Xu, C. Gui, and M. D. Fox, "Level set evolution without re-initialization: A new variational formulation," Proc. IEEE Conf. Computer Vision and Pattern Recognition(CVPR), Vol.1, pp. 430-436, 2005.
11 M. M. Schulze, N. Hutchings, and T. L. Simpson, "The Use of Fractal Analysis and Photometry to Estimate the Accuracy of Bulbar Redness Grading Scales," Invest Ophth Vis Sci, Vol.49, pp. 1398-1406, April 2008.   DOI   ScienceOn
12 Y. Sato, S. Nakajima, N. Shiraga, H. Atsumi, S. Yoshida, T. Koller, G. Gerig, and R. Kikinis, "Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images," Med Image Anal, Vol 2 No. 2, pp. 143-68, 1998.   DOI   ScienceOn
13 N. Funabiki, M. Isogai, T. Higashino, and M. Oda, "An Eye-Contour Extraction Algorithm from Face Image using Deformable Template Matching," Mem Fac Eng Okayama Univ, Vol.40, pp. 2006.
14 V. Vezhnevets, V. Sazonov, and A. Andreeva, "A survey on pixel-based skin color detection techniques," Proc. Graphicon-2003, pp. 85-92, 2003.
15 M. H. Khosravi and R. Safabakhsh, "Human eye sclera detection and tracking using a modified time-adaptive self-organizing map," Pattern Recogn Vol.41, pp.2571-2594, 2008.   DOI   ScienceOn
16 P. Fieguth and T. Simpson, "Automated Measurement of Bulbar Redness," Invest Ophthalmol Vis Sci, Vol.43 , pp. 340-347, February 2002.