Texture classification of retinal layers in optical coherence tomography

IFMBE Proceedings

Volumn 16, Issue 1, 2007, Pages 847-850

  Baroni, Maurizio ^a   Diciotti, S ^a   Evangelisti, A ^a   Fortunato, P ^a   La Torre, A ^a  

^a UNIVERSITY OF FLORENCE   (Italy)

Author keywords

Image segmentation; Neural networks; Optical coherence tomography; Texture analysis

Indexed keywords

DISEASE CONTROL; IMAGE ANALYSIS; IMAGE SEGMENTATION; IMAGE TEXTURE; NEURAL NETWORKS; OPHTHALMOLOGY; OPTICAL TOMOGRAPHY; TEXTURES; TISSUE; TOMOGRAPHY;

BIOLOGICAL TISSUES; CO-OCCURENCE MATRIX; COMPUTER METHODS; IMAGING TECHNOLOGY; NONINVASIVE VISUALIZATION; QUANTITATIVE CHARACTERIZATION; TEXTURE ANALYSIS; TEXTURE CLASSIFICATION;

MULTILAYER NEURAL NETWORKS;

EID: 85007140087     PISSN: 16800737     EISSN: 14339277     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-73044-6_220     Document Type: Conference Paper

References (18)

1. Huang D, Swanson EA, Lin CP, et al. (1991) Optical Coherence Tomography. Science 254: 1178-1181.
2. Brezinski M. (2006) Optical Coherence Tomography: principles and applications. Academic Press, New York.
3. Schuman JS, Puliafito C, Fujimoto JG. (2004) Optical coherence tomography of ocular diseases. 2nd ed. Thorofare, NJ.
4. Ray R., Stinnett S.S., Jaffe G.J. (2005) Evaluation of Image Artefact Produced by Optical Coherence Tomography of Retinal Pathology. Am J Ophthalmol 139:18-29.
5. Haralick R.M. (1979) Statistical and Structural Approaches to Texture. Proc.IEEE 67:786-804.
6. Baroni M., Fortunato P., La Torre A. (2007) Towards quantitative analysis of retinal features in OCT. Med. Eng. & Phys. 29, 432-441.
7. Knighton R.W. and Huang X.R. (1999) Directional and spectral reflectance of the rat retinal nerve fiber layer. Invest Ophthalmol Vis Sci. 40: 639-47.
8. Schmitt JM, Xiang SH, Yung KM (1999) Speckle in optical coherence Tomography. J. Biomed. Optics 4: 95-100.
9. Koozekanani D., Boyer K., and Roberts C. (2001) Retinal thickness measurements from optical coherence tomography using a Markov boundary model. IEEE Trans. Med. Imaging 20: 900–16.
10. Shahidi M., Wang Z., Zelkha R. (2005) Quantitative Thickness Measurement of Retinal Layers Imaged by Optical Coherence Tomography. Am J Ophthalmol 139:1056–61.
11. Cabrera Fernández D., Salinas H.M., Puliafito C.A. (2005) Automated detection of retinal layer structures on optical coherence tomography images. Opt. Express 13: 10200-216.
12. Perona P., Malik J. (1990). Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Anal. Mach. Intell. 12, 629-639
13. J. S. Weszka, C. R. Dyer, and A. Rosenfield (1976) A comparative study of texture measures for terrain classification. IEEE Trans. Syst., Man, Cybern., vol. SMC-6.
14. C.-M. Wu, Y.-C. Chen, and K.-S. Hsieh (1992) Texture features for classification of ultrasonic liver images. IEEE Trans. Med. Imag., 11: 141–152.
15. T. Ojala, M. Pietikainen, and D. Harwood (1996) A comparative study of texture measures with classification based on feature distributions. Pattern Recogn. 29: 51–59.
16. Bishop C. (1995) Neural networks for pattern recognition. Oxford Univ. Press, New York.
17. Bocchi L., Coppini G., De Domenicis R., Valli G. (1997) Tissue characterization from X-ray images. Med. Eng. & Phys. 19: 336-42.
18. Binder T, Sussner M, Moertl D. et al.(1999) Artificial neural network and spatial temporal linking for automated endocardial contour detection on echocardiograms. Ultrasound in Med. & Biol. 25: 1069-76.