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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 2, Iss. 10 — Oct. 1, 2011
  • pp: 2821–2836

Morphological analysis of optical coherence tomography images for automated classification of gastrointestinal tissues

P. Beatriz Garcia-Allende, Iakovos Amygdalos, Hiruni Dhanapala, Robert D. Goldin, George B. Hanna, and Daniel S. Elson  »View Author Affiliations

Biomedical Optics Express, Vol. 2, Issue 10, pp. 2821-2836 (2011)

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The impact of digestive diseases, which include disorders affecting the oropharynx and alimentary canal, ranges from the inconvenience of a transient diarrhoea to dreaded conditions such as pancreatic cancer, which are usually fatal. Currently, the major limitation for the diagnosis of such diseases is sampling error because, even in the cases of rigorous adherence to biopsy protocols, only a tiny fraction of the surface of the involved gastrointestinal tract is sampled. Optical coherence tomography (OCT), which is an interferometric imaging technique for the minimally invasive measurement of biological samples, could decrease sampling error, increase yield, and even eliminate the need for tissue sampling provided that an automated, quick and reproducible tissue classification system is developed. Segmentation and quantification of ophthalmologic pathologies using OCT traditionally rely on the extraction of thickness and size measures from the OCT images, but layers are often not observed in nonopthalmic OCT imaging. Distinct mathematical methods, namely Principal Component Analysis (PCA) and textural analyses including both spatial textural analysis derived from the two-dimensional discrete Fourier transform (DFT) and statistical texture analysis obtained independently from center-symmetric autocorrelation (CSAC) and spatial grey-level dependency matrices (SGLDM), have been previously reported to overcome this problem. We propose an alternative approach consisting of a region segmentation according to the intensity variation along the vertical axis and a pure statistical technique for feature quantification, i.e. morphological analysis. Qualitative and quantitative comparisons with traditional approaches are accomplished in the discrimination of freshly-excised specimens of gastrointestinal tissues to exhibit the feasibility of the proposed method for computer-aided diagnosis (CAD) in the clinical setting.

© 2011 OSA

OCIS Codes
(110.2960) Imaging systems : Image analysis
(110.4500) Imaging systems : Optical coherence tomography
(170.3880) Medical optics and biotechnology : Medical and biological imaging

ToC Category:
Image Processing

Original Manuscript: August 4, 2011
Revised Manuscript: September 9, 2011
Manuscript Accepted: September 15, 2011
Published: September 22, 2011

Virtual Issues
Advances in Optics for Biotechnology, Medicine, and Surgery (2011) Biomedical Optics Express

P. Beatriz Garcia-Allende, Iakovos Amygdalos, Hiruni Dhanapala, Robert D. Goldin, George B. Hanna, and Daniel S. Elson, "Morphological analysis of optical coherence tomography images for automated classification of gastrointestinal tissues," Biomed. Opt. Express 2, 2821-2836 (2011)

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