The future of surgical planning
Applying deep learning technologies to aid surgeons
From scans to 3D models
We use standard-of-care CT and MRI scans as the input into our algorithms. We then apply interactive machine learning to extract the patient’s anatomy from the scan, which is viewed as a 3D model.
Enhanced operative planning
Surgeons use this information to decide on the best possible plan for the patient. The 3D model can be viewed on mobile devices, in Virtual Reality, 3D printed, and used as part of augmented reality applications.
Improved surgical outcomes
Through improved surgical planning we reduce the risk of complications, allowing more patients to be selected for minimally invasive surgery. The result is shorter hospital stays and reduced costs to healthcare providers.
Meet the team
Innersight Labs is a multi-disciplinary team of passionate people with the unique skill-set to create the world's leading surgery planning platform.
Eoin is an Enterprise Fellow of the Royal Academy of Engineering with a PhD in Computational Physiology from the University of Oxford. He previously worked as a researcher on cardiac medical devices at St Thomas’ Hospital and King's College London.
Neha TannaBusiness Development
Neha is a practicing doctor and holds an MBA from the London Business School. She also has three years business development experience at Merck Pharmaceuticals.
Lorenz BergerChief Scientist
Lorenz holds a PhD in Computer Science from the University of Oxford and previously worked as a Machine Learning researcher at University College London.
Matt holds a PhD in Computer Science from the University of Oxford and previously worked as a Machine Learning engineer at Tesla.
Andrew has over 30 years’ experience as a senior manager, non-executive director, and investor in medical imaging and software businesses.
Sebastien OurselinScientific Advisor
Seb, a Professor of Medical Image Computing, heads the School of Biomedical Engineering and Imaging Sciences at King's College London. He has 15 years' experience of translating surgical planning research into clinical practice.