Blood moon and image analysis

When the blood moon passed by our skies some weeks ago it was impossible for our CTO not to notice the resemblance of it to the retinal images. He has been so committed to improve the mathematical model that we implemented at Braviithi using the images for training that his eyes were connecting big red circles images to the ocular images with no effort. The blood moon was an astonishing event that reminded us how marvelous our universe is, and how much we still have to learn from it. The blood moon images will help multiple astronomic and mathematical studies and also amaze this and future generations. As well, the retinal images should be use in their full potential, to help doctors, patients and the medical industry in general to accelerate and improve diagnostics.

Creative and knowledgeable programmers, developers, mathematicians and and physicists are needed to reach the full potential and extract all the possible information from these images. Braviithi’s mathematical model has many advantages, one of them is that only needs 10 images to get 90% accuracy while machine learning needs more images for the trainings. Moreover, Braviithi technology allows the use of different cameras, adding variety to the images’ sources, while machine learning or deep learning can only use some types of cameras, restricting the doctors’ options. At Braviithi we aim to embrace the full potential of image analysis and improve patients lives and support health care professionals.