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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 4, Iss. 10 — Oct. 1, 2013
  • pp: 2032–2050

Multi-penalty conditional random field approach to super-resolved reconstruction of optical coherence tomography images

Ameneh Boroomand, Alexander Wong, Edward Li, Daniel S. Cho, Betty Ni, and Kostandinka Bizheva  »View Author Affiliations

Biomedical Optics Express, Vol. 4, Issue 10, pp. 2032-2050 (2013)

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Improving the spatial resolution of Optical Coherence Tomography (OCT) images is important for the visualization and analysis of small morphological features in biological tissue such as blood vessels, membranes, cellular layers, etc. In this paper, we propose a novel reconstruction approach to obtaining super-resolved OCT tomograms from multiple lower resolution images. The proposed Multi-Penalty Conditional Random Field (MPCRF) method combines four different penalty factors (spatial proximity, first and second order intensity variations, as well as a spline-based smoothness of fit) into the prior model within a Maximum A Posteriori (MAP) estimation framework. Test carried out in retinal OCT images illustrate the effectiveness of the proposed MPCRF reconstruction approach in terms of spatial resolution enhancement, as compared to previously published super resolved image reconstruction methods. Visual assessment of the MPCRF results demonstrate the potential of this method in better preservation of fine details and structures of the imaged sample, as well as retaining the sharpness of biological tissue boundaries while reducing the effects of speckle noise inherent to OCT. Quantitative evaluation using imaging metrics such as Signal-to-Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Equivalent Number of Looks (ENL), and Edge Preservation Parameter show significant visual quality improvement with the MPCRF approach. Therefore, the proposed MPCRF reconstruction approach is an effective tool for enhancing the spatial resolution of OCT images without the necessity for significant imaging hardware modifications.

© 2013 OSA

OCIS Codes
(100.0100) Image processing : Image processing
(110.4500) Imaging systems : Optical coherence tomography
(330.6130) Vision, color, and visual optics : Spatial resolution

ToC Category:
Image Processing

Original Manuscript: June 3, 2013
Revised Manuscript: August 6, 2013
Manuscript Accepted: August 7, 2013
Published: September 6, 2013

Ameneh Boroomand, Alexander Wong, Edward Li, Daniel S. Cho, Betty Ni, and Kostandinka Bizheva, "Multi-penalty conditional random field approach to super-resolved reconstruction of optical coherence tomography images," Biomed. Opt. Express 4, 2032-2050 (2013)

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