I was listening to @jeremy on TWIML last week, and at the end of the talk he mentions the lack of publicly available medical imaging datasets. Applying deep learning to medical images is my research area, so I am intimately aware of the problem and thought I could contribute what I’ve learned about the practice back to the community.
I created a blog post with my thoughts on how to get started with using deep learning on medical images, specifically magnetic resonance (MR) and computed tomography (CT) images. I overview the two imaging modalities, suggest several publicly available datasets, discuss some techniques for data wrangling and preprocessing (with example scripts), and finally build a small 3D deep learning model using the fastai API.
It turned out a bit longer than expected, and while there is a lot more information to cover, this should (hopefully) help people get started with applying deep learning to structural MR and CT images. I know there has been some previous discussion on here (see here, here, and here for some previous discussion). But I’d be happy to answer any questions regarding the blog post or more general questions regarding working with medical images.
Just wanted to say thanks to everyone who has helped build the fastai package, it’s awesome!