Medical Image Analysis with Deep Learning — III

Note: This is a 4 part article and you can find the other articles via these links (part 1, part 2, this, part 4). I have also put together collection of these in a small booklet available via amazon, if you would like a physical copy. Please reach out to me if you have feedback to improve and provide this information to all.

In the last article we will talk about basics of deep learning from the lens of Convolutional Neural Nets. In this article we will focus — basic deep learning using Keras and Theano. We will do 2 examples one using keras for basic predictive analytics and other a simple example of image analysis using VGG.

I have realized that this topic is broad and deep and will need a few more articles. In the next few articles we will discuss difference between DICOM and NIFTI formats for medical imaging , expand our learning further and discuss how to use deep learning for 2D lung segmentation analysis. We then move to analyze 3D lung segmentation. We will also discuss how medical image analysis was done prior deep learning and how we can do it now. I would also like to welcome and thank my new partners who will help me with putting this all together — Flavio Trolese, Partner at 4Quant, Kevin Mader, Co-founder of 4Quant and Lecturer at ETH Zurich and Cyriac Joshy.