Resource Catalog
Explore datasets, tools and resources across our research areas.
A software package for segmenting the boundaries of cone photoreceptors in non-confocal adaptive optics images such as split detection. This software was primarily developed by Jianfei Liu, Andrei Volkov, and Johnny Tam, with research support from the Intramural Research Program of the National Institutes of Health, National Eye Institute. Additional details about the algorithms used can be found in the reference listed below.
A software implementation for recovering the individual retinal pigment epithelial (RPE) cells from single noisy adaptive optics optical coherence tomography (AOOCT) images. This software was primarily developed by Vineeta Das and Johnny Tam, with research support from Intramural Research Program of the National Institutes of Health, National Eye Institute. Additional details about the algorithms used can be found in the reference listed below.
Still life painting comprises a wealth of data on visual perception. Prior work has shown that the color statistics of objects show a marked bias for warm colors. Here, we ask about the relative chromatic contrast of these object-associated colors compared to background colors in still life paintings.
A software package for detecting cone photoreceptor cells from non-confocal split detection adaptive optics images using machine learning.
A software package for segmenting cone photoreceptor cells from non-confocal split detection adaptive optics images using machine learning.
