Kia ora e hoa,
My brief absence has made me realise how much I miss landing in your inbox every Sunday morning with a topic that I am passionate about. This feeling makes me want to come back sooner, and so, here I am.
Grading retinal images for diabetic retinopathy (DR) is an image classification problem. We have images, and we need to grade them into these possible categories: healthy, background DR referrable DR.
Why is this useful?
In Aotearoa, 250,000 people have diabetes and a quarter have DR. Fortunately, individuals with diabetes are screened with routine retinal imaging taken at least biennially. But, unfortunately, that’s a lot of images to grade! On top of this, grading these images requires experts — of which there are too few.
Can AI plug this gap?
But first, what is deep learning? Deep learning is a subset of machine learning. Machine learning is where computers are programmed to learn from data. Machine learning includes methods from statistics like regression and optimisation from calculus.
Deep learning takes these mathematics principles to the next level. Taking inspiration from the human brain’s architecture, deep learning involves virtual neurons that interact and interconnect. An example of what deep learning can do is classify images.