136 results about "Retinal Disorder" patented technology

A visible and infrared light powered retinal implant is disclosed that is implanted into the subretinal space for electrically inducing formed vision in the eye. The retinal implant includes a stacked microphotodetector arrangement having an image sensing pixel layer and a voltage and current gain adjustment layer for providing variable voltage and current gain to the implant so as to obtain better low light implant performance than the prior art, and to compensate for high retinal stimulation thresholds present in some retinal diseases. A first light filter is positioned on one of the microphotodetectors in each of the image sensing pixels of the implant, and a second light filter is positioned on the other of the microphotodetectors in the image sensing pixel of the implant, each of the microphotodetectors of the pixel to respond to a different wavelength of light to produce a sensation of darkness utilizing the first wavelength, and a sensation of light using the second wavelength, and a third light filter is positioned on a portion of the voltage and current gain adjustment layer that is exposed to light, to allow adjustment of the implant voltage and current gain of the device by use of a third wavelength of light.

In the context of the early detection and monitoring of eye diseases, such as glaucoma and diabetic retinopathy, the use of optical coherence tomography presents the difficulty, with respect to blood vessel segmentation, of weak visibility of vessel pattern in the OCT fundus image. To address this problem, a boosting learning approach uses three-dimensional (3D) information to effect automated segmentation of retinal blood vessels. The automated blood vessel segmentation technique described herein is based on 3D spectral domain OCT and provides accurate vessel pattern for clinical analysis, for retinal image registration, and for early diagnosis and monitoring of the progression of glaucoma and other retinal diseases. The technique employs a machine learning algorithm to identify blood vessel automatically in 3D OCT image, in a manner that does not rely on retinal layer segmentation.