Random forests in medical image computing
The Random Forests algorithm had a substantial impact on medical image computing over the last decade. This chapter presents basic algorithmic details, some variations proposed in the recent years and applications in medical image computing. Arguably, Random Forests' main impact was on the analysis tasks that required understanding spatial context within the images.
Authors: Ender Konukoglu, Ben Glocker
Handbook of Medical Image Computing and Computer Assisted Intervention/January 2020
We take a specific angle and view Random Forests as a machine learning tool that can integrate contextual information. We position the algorithm and its contributions within the larger field from this respect. Lastly, we briefly discuss how Random Forests and deep learning methods relate to each other and how they differ.