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Article
Intensity Inhomogeneity Correction of Macular OCT using N3 and Retinal Flatspace
Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on
  • Andrew Lang, The Johns Hopkins University
  • Aaron Carass, The Johns Hopkins University
  • Bruno Jedynak, Portland State University
  • Sharon D. Solomon, The Johns Hopkins Hospital
  • Peter Calabresi, The Johns Hopkins Hospital
  • Jerry L. Prince, The Johns Hopkins University
Document Type
Article
Publication Date
4-1-2016
Subjects
  • Optical coherence tomography,
  • Retina -- Tomography,
  • Image segmentation,
  • Biomedical imaging
Disciplines
Abstract

As optical coherence tomography (OCT) has increasingly become a standard modality for imaging the retina, automated algorithms for processing OCT data have become necessary to do large scale studies looking for changes in specific layers. To provide accurate results, many of these algorithms rely on the consistency of layer intensities within a scan. Unfortunately, OCT data often exhibits inhomogeneity in a given layer's intensities, both within and between images. This problem negatively affects the performance of segmentation algorithms and little prior work has been done to correct this data. In this work, we adapt the N3 framework for intensity inhomogeneity correction, which was originally developed to correct MRI data, to work for macular OCT data. We first transform the data to a flattened macular space to create a template intensity profile for each layer giving us an accurate initial estimate of the gain field. N3 will then produce a smoothly varying field to correct the data. We show that our method is able to both accurately recover synthetically generated gain fields and improves the stability of the layer intensities.

DOI
10.1109/ISBI.2016.7493243
Persistent Identifier
http://archives.pdx.edu/ds/psu/19547
Citation Information
A. Lang, A. Carass, B. M. Jedynak, S. D. Solomon, P. A. Calabresi and J. L. Prince, "Intensity inhomogeneity correction of macular OCT using N3 and retinal flatspace," 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), Prague, 2016, pp. 197-200.