InnerEye is a research project that uses state of the art machine learning technology to build innovative tools for the automatic, quantitative analysis of three-dimensional radiological images. Project InnerEye turns radiological images into measuring devices.
Satya Nadella, keynote at Microsoft IGNITE 2016.
Project InnerEye develops machine learning techniques for the automatic delineation of tumors as well as healthy anatomy in 3D radiological images. The InnerEye technology may enable: 1. extraction of targeted radiomics measurements for quantitative radiology, 2. efficient contouring for radiotherapy planning, 3. precise surgery planning and navigation. In practice, Project InnerEye turns multi-dimensional radiological images into measuring devices.
Project InnerEye builds upon many years of research in computer vision and machine learning. It employs algorithms such as Deep Decision Forests (as used already in Kinect and Hololens) as well as Convolutional Neural Networks (as available in CNTK) for the automatic, voxel-wise segmentation of medical images.
The technology is being designed with the guidance of expert medical practitioners. The results of our machine learning operations can be readily refined and adjusted by expert clinical researchers until they are completely satisfied with the results. They maintain full control of the results at all times.