Project InnerEye – Medical Imaging AI to Empower Clinicians

Project InnerEye – Medical Imaging AI to Empower Clinicians

Established: October 7, 2008

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.

“…We are pursuing AI so that we can empower every person and every institution that people build with tools of AI so that they can go on to solve the most pressing problems of our society and our economy. That’s the pursuit.”.

Satya Nadella, keynote at Microsoft IGNITE 2016.

Project InnerEye @ HIMSS 2018

Project InnerEye will be at HIMSS 2018 in Las Vegas. Please come and visit us if you wish to know more.

Project description

Project InnerEye develops machine learning techniques for the automatic delineation of tumors as well as healthy anatomy in 3D radiological images. This enables: 1. extraction of targeted radiomics measurements for quantitative radiology, 2. fast 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 analysis of medical images.

The technology is designed to be of assistance to expert medical practitioners. The results of our machine learning operations can be readily refined and adjusted by expert clinicians until completely satisfied with the results. The doctors maintain full control of the results at all times.

Our algorithms are deployed as intelligent Azure services and they are intended to be consumed by third-party medical software manufacturers. The InnerEye cloud API is designed to be integrated within third-party software, to augment it with Microsoft’s world-leading AI capabilities.

Slides from RSNA17 Plenary Presentation

The slide deck Antonio presented at the plenary session at RSNA17 can be downloaded from here (118MB)

Demo videos



Please send an email to if you wish to integrate the InnerEye cloud API within your software, or would like further information on this project.