June 2020
Volume 61, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2020
Fully automatic separation of three capillary plexuses in the macular region
Author Affiliations & Notes
  • Julia Schottenhamml
    Friedrich-Alexander-University Erlangen-Nuremberg, Germany
  • Stefan B Ploner
    Friedrich-Alexander-University Erlangen-Nuremberg, Germany
  • Eric Moult
    Massachusetts Institute of Technology, Massachusetts, United States
  • Jay S Duker
    New England Eye Center at Tufts Medical Center, Massachusetts, United States
  • Nadia K Waheed
    New England Eye Center at Tufts Medical Center, Massachusetts, United States
  • James G Fujimoto
    Massachusetts Institute of Technology, Massachusetts, United States
  • Andreas Maier
    Friedrich-Alexander-University Erlangen-Nuremberg, Germany
  • Footnotes
    Commercial Relationships   Julia Schottenhamml, None; Stefan Ploner, IP related to VISTA (P), Optovue (C); Eric Moult, IP related to VISTA (P); Jay Duker, Carl Zeiss Meditec (F), Carl Zeiss Meditec (C), Optovue (F), Optovue (C), Topcon (F), Topcon (C); Nadia Waheed, Carl Zeiss Meditec (F), Heidelberg (F), MVRF (F), Nidek (F), Optovue (C), Topcon (F); James Fujimoto, Carl Zeiss Meditec (P), Optovue (I), Optovue (P), Optovue (C), Topcon (F); Andreas Maier, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 482. doi:
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    • Get Citation

      Julia Schottenhamml, Stefan B Ploner, Eric Moult, Jay S Duker, Nadia K Waheed, James G Fujimoto, Andreas Maier; Fully automatic separation of three capillary plexuses in the macular region. Invest. Ophthalmol. Vis. Sci. 2020;61(7):482.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : The retinal vascular system in the macular region can be divided into three capillary plexuses, namely the superficial vascular plexus (SVP), intermediate (ICP) and deep capillary plexus (DCP). Being able to create an adequate OCTA visualization of these three plexuses could improve the understanding of various retinal diseases affecting the blood vessels. We therefore propose a fully automatic algorithm to compute shadow artifact compensated projections of the SVP, ICP and DCP.

Methods : In order to compute the projection boundaries, the bottom of the Nerve Fiber Layer (NFL), Inner Plexiform Layer (IPL) and Outer Plexiform Layer (OPL) is first segmented with a multi-Dijkstra approach. This algorithm generates a graph from the B-Scans and computes the edge weights using the axial gradient. Improved reliability is achieved by computing the shortest paths for the three layer boundaries simultaneously with the spatial constraints such that the NFL/ IPL/ OPL is the top/ middle/ bottom boundary. This ensures that there are no discontinuities in the layer boundaries and that they have the correct spatial order. Shadow artifacts are compensated using an algorithm by Ploner et al (ARVO 2017). Finally the axial spreads of the plexuses are defined as [NFL-1; max(IPL-2, NFL-1)] for the SVP, [IPL-0.5;IPL+2] for the ICP and [mean(2/3*IPL+1/3*OPL)+2; OPL-3] and the associated enface projections are created using maximum projection.

Results : Qualitative results for the segmentation and the enface projections are shown in Figure 1 and 2 respectively.

Conclusions : Our fully automatic segmentation enables enface projections of individual capillary plexuses, opening up new research directions.

This is a 2020 ARVO Annual Meeting abstract.

 

Enface projections from NFL to OPL (1,5) and of the three capillary plexuses (SVP: 2,6; ICP:3,7; DCP 4,8). Tiles 1-4 and 5-8 show OCTA volume projections without and with shadow artifact compensation. A: 28 y/o healthy; B: 52 y/o diabetes mellitus without diabetic retinopathy; C: 67 y/o proliferative diabetic retinopathy.

Enface projections from NFL to OPL (1,5) and of the three capillary plexuses (SVP: 2,6; ICP:3,7; DCP 4,8). Tiles 1-4 and 5-8 show OCTA volume projections without and with shadow artifact compensation. A: 28 y/o healthy; B: 52 y/o diabetes mellitus without diabetic retinopathy; C: 67 y/o proliferative diabetic retinopathy.

 

B-Scans extracted at the position of the yellow lines in Figure 1. 1: original OCT B-Scan; 2: projection boundaries (top: dotted, bottom: solid) on OCTA B-Scan; 3: segmentation lines from the multi-Dijkstra approach; 4: projection boundaries on shadow artifact compensated OCTA B-Scan. Arrows show vessel correspondences between both figures.

B-Scans extracted at the position of the yellow lines in Figure 1. 1: original OCT B-Scan; 2: projection boundaries (top: dotted, bottom: solid) on OCTA B-Scan; 3: segmentation lines from the multi-Dijkstra approach; 4: projection boundaries on shadow artifact compensated OCTA B-Scan. Arrows show vessel correspondences between both figures.

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