1 / 13

Epiretinal Membrane Detection

Epiretinal Membrane Detection. Bhavna Antony. Method . Detect ILM Refine ILM surface detection search for 2 surfaces i.e. ERM and ILM Edge cost terms derived from 2-D edge detector because volumes have few slices. Regional term looks for bright bounding surfaces and dark spaces.

bart
Download Presentation

Epiretinal Membrane Detection

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Epiretinal Membrane Detection Bhavna Antony

  2. Method • Detect ILM • Refine ILM surface detection • search for 2 surfaces i.e. ERM and ILM • Edge cost terms derived from 2-D edge detector because volumes have few slices. • Regional term looks for bright bounding surfaces and dark spaces. • Works well for clear subretinal spaces, fails in the case of pockets that have mueller cells.

  3. Status of Flattening Paper Previously used two 3-D splines Now using one 3-D spline, followed by 2-D spline estimating “ripple” in y-direction

  4. Original Surface

  5. After 3-D spline fit and flattening After 2-D spline fit and flattening

  6. Use dual direction scans to estimate artifact free OCT volume Horizontal Scan 128 Vertical Scan 128

  7. 128 512

More Related