Estimating Retinal Sensitivity Using Optical Coherence Tomography With Deep-Learning Algorithms in Macular Telangiectasia Type 2

Macular telangiectasia type 2 (MacTel) is a neurodegenerative disease affecting the parafoveal region of the retina, causing loss of central vision. Microperimetry testing is used to monitor progression of vision loss in patients with MacTel, during which multiple points on the retina are tested for sensitivity to light. Recent advances in imaging technology have correlated the focal light sensitivity defects that occur with MacTel to at least one structural defect, ellipsoid zone loss. We hypothesized that a deep learning model could be trained to estimate retinal sensitivity using structural details identified on optical coherence tomography (OCT) images and microperimetry data, providing a detailed high-resolution functional map of the retina that may be useful for research purposes or when microperimetry is not feasible.

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