About us

Our vision is that every human being has the opportunity for a timely diagnosis, high-quality care, and a longer, healthier life.

At Subtle Medical, we are committed to transforming the healthcare ecosystem by building and delivering responsible AI solutions that create a measurable impact on the radiology workflow and patient experience. We exist to empower physicians and patients with safe and timely medical imaging that leads to improved outcomes and a higher quality of life for all.

Subtle Medical Is the world leader in applying deep learning to the acquisition of medical images in order to enable faster, safer, and smarter medical imaging.

8

FDA-cleared Software Solutions

30+

Issued and/or Pending Patents

20+

Peer Reviewed Papers

$50M

Raised Over

Our Story:

Subtle Medical was born out of Stanford University by founders, Greg Zaharchuk, MD, Ph.D., Neuroradiologist and Professor at Stanford, and Enhao Gong, Ph.D., a deep learning scientist. Enhao was studying under Dr. Zaharchuk during his Ph.D. program, where they discovered their joint passion for improving the quality and access of medical imaging and recognized the power of deep learning to allow them to do so. This ignited the ambition to start Subtle Medical, and it was eventually accepted into the elite Stanford StartX program. With over $50 million raised to date, Subtle Medical has over 70 full time employees and has been deployed on close to a thousand scanners in multiple countries across the globe.

Our Commitment to Environmental Sustainability:

Sustainable actions help make a tangible difference in society. When we focus on sustainability, the entire world benefits and gets to live in cleaner, more healthy living conditions. Subtle’s software solutions enable increased imaging speed and quality on your existing scanners, allowing you to delay or optimize capital purchases and invest in scanners more wisely. Our software allows you to reduce your overall carbon footprint and help make every day Earth Day.

Leadership

Enhao Gong, PhD

Founder & CEO

Greg Zaharchuk, MD, PhD

Founder & Neuroradiologist

Ajit Shankaranarayanan, PhD

Chief Product Officer

Josh Gurewitz

Chief Commercial Officer

Anna Menyhart-Borroni

Head of Marketing

Praveen Gulaka, PhD

Head of Clinical

Suzie Bash, MD

Medical Director of Neuroradiology, San Fernando Valley Interventional Radiology, RadNet Inc.

Michael Brant-Zawadzki,
MD, FACR

Executive Medical Director, Hoag Memorial Hospital

Paul Chang, MD

Professor of Radiology, Vice Chair, Radiology Informatics, University of Chicago

Florian Knoll, PhD

Adjunct Assistant Professor, Department of Radiology, NYU Langone Health

Jessica Leung, MD

Section Chief, Women's Imaging, Department of Radiology, MD Anderson Cancer Center

Satoshi Minoshima, MD, PhD

Chair, Department of Radiology & Imaging Sciences, University of Utah Hospital

John M. Pauly, PhD

Professor of Engineering, Stanford University, Co-Director, MR Systems Research Laboratory

Dr. Bruce Rosen, MD, PhD

Director, Biomedical Imaging, Massachusetts General Hospital

Kawin Setsompop, PhD

Associate Professor of Radiology (Radiological Sciences Laboratory) and Electrical Engineering, Stanford University

Lawrence Tanenbaum,
MD, FACR

Chief Technology Officer, Director of Advanced Imaging, Vice President, RadNet Inc.

Max Wintermark, MD, MA, MBA

Chief of Neuroradiology, Professor of Radiology, Stanford School of Medicine

Investors

Partners

Explore Who We’ve Integrated With:

Siemens Healthineers

SubtleMR™ will be available on the Siemens Healthineers OpenRecon interface starting in mid- 2022, offering the option of DL (deep learning) post-processing for denoising and increased sharpness for almost all MRI sequences on Siemens MRI machines globally.

Aidoc

The addition of SubtlePET™ and SubtleMR™ to the Aidoc AI platform will create an end-to-end solution and the first joint offering of AI for both image acquisition and triage.

Bayer

Subtle Medical and Bayer are working together to explore opportunities to leverage our SubtleGAD™ technology for optimal image quality and acquisition for low dose contrast-enhanced MRI.