3D Mapping of Choroidal Thickness from OCT B-Scans

  • Simão P. Faria
  • Susana Penas
  • Luís Mendonça
  • Jorge A. Silva
  • Mendonça Ana Maria 
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 27)


The choroid is the middle layer of the eye globe located between the retina and the sclera. It is proven that choroidal thickness is a sign of multiple eye diseases. Optical Coherence Tomography (OCT) is an imaging technique that allows the visualization of tomographic images of near surface tissues like those in the eye globe. The automatic calculation of the choroidal thickness reduces the subjectivity of manual image analysis as well as the time of large scale measurements.

In this paper, a method for the automatic estimation of the choroidal thickness from OCT images is presented. The pre-processing of the images is focused on noise reduction, shadow removal and contrast adjustment. The inner and outer boundaries of the choroid are delineated sequentially, resorting to a minimum path algorithm supported by new dedicated cost matrices. The choroidal thickness is given by the distance between the two boundaries. The data are then interpolated and mapped to an infrared image of the eye fundus.

The method was evaluated by calculating the error as the distance from the automatically estimated boundaries to the boundaries delineated by an ophthalmologist. The error of the automatic segmentation was low and comparable to the differences between manual segmentations from different ophthalmologists.


Optical Coherence Tomography Choroidal thickness Medical image analysis 



This work is supported by Project “NanoSTIMA: Macro-to-Nano Human Sensing: Towards Integrated Multimodal Health Monitoring and Analytics/NORTE-01-0145-FEDER-000016”, financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF).


  1. 1.
    Alonso-Caneiro, D., Read, S.A., Collins, M.J.: Automatic segmentation of choroidal thickness in Optical Coherence Tomography. Biomed. Opt. Express 4(12), 2795–2812 (2013)CrossRefGoogle Scholar
  2. 2.
    Danesh, H., Kafieh, R., Rabbani, H., Hajizadeh, F.: Segmentation of choroidal boundary in enhanced depth imaging OCTs using a multiresolution texture based modeling in graph cuts. Comput. Math. Methods Med. 2014 (2014). Article ID 479268, 9 pagesGoogle Scholar
  3. 3.
    González-López, A., Remeseiro, B., Ortega, M., Penedo, M.G.: Choroid characterization in EDI OCT retinal images based on texture analysis. In: Proceedings of the 7th International Conference on Agents and Artificial Intelligence, ICAART 2015, vol. 2, pp. 269–276 (2015)Google Scholar
  4. 4.
    Rahman, W., Chen, F.K., Yeoh, J., Patel, P., Tufail, A., Da Cruz, L.: repeatability of manual subfoveal choroidal thickness measurements in healthy subjects using the technique of enhanced depth imaging optical coherence tomography. Invest. Ophthalmol. Vis. Sci. 52(5), 2267–2271 (2011). doi: 10.1167/iovs.10-6024 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Simão P. Faria
    • 3
  • Susana Penas
    • 4
  • Luís Mendonça
    • 5
  • Jorge A. Silva
    • 2
    • 3
  • Mendonça Ana Maria 
    • 1
    • 3
  1. 1.Faculty of Engineering, Department of Electrical and Computer EngineeringUniversity of PortoPortoPortugal
  2. 2.Faculty of Engineering, Department of Informatics EngineeringUniversity of PortoPortoPortugal
  3. 3.INESC-TECPortoPortugal
  4. 4.Department of OphthalmologySão João Hospital CentrePortoPortugal
  5. 5.Department of OphthalmologyHospital of BragaBragaPortugal

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