Subtle Medical
United States
- Menlo Park, California
- 03/06/2026
- Series C
- $33,000,000
Subtle Medical is a medical imaging software company. Our goal is to improve the quality, value, and accessibility of medical imaging by significantly reducing cost, imaging time, and radiation dose. We use the state-of-art proprietary deep learning AI algorithms to renovate the radiology workflow to deliver faster, safer and smarter imaging for imaging providers and the patients they serve.
- Industry Hospital & Health Care
- Website https://subtlemedical.com/
- LinkedIn https://www.linkedin.com/company/subtlemedical/
Related People
Enhao GONGFounder
United States -
San Francisco Bay Area
Looking forward to meet you and brain storm how AI can reshape the world.
Founder&CEO @ Subtle Medical:
- Deep Learning to improve the efficiency and value Medical Imaging
PhD in EE@Stanford:
- Medical Imaging (MRI), Deep Learning, Compressed Sensing, Data Driven Image Processing, Machine Learning
Co-founder @ Polarr:
- Deep Learning, Computer Vision, Image Processing, Image Rendering
Technical Experience: Imaging Systems, Machine Learning, Deep Learning, Computational Imaging, Signal Processing, Neural/Bio Signal Processing, Optical Imaging, Super Resolution
Operation Experience: Business Development, Entrepreneurship, Sales Management, Business Planning, Finance, Start-ups, Product Development, Budgeting, Operations Management, Management Consulting.
About me:
As a Stanford Graduate Fellow, I completed my PhD in Electrical Engineering at Stanford. My research is focused on deep learning in medical imaging. Our recent work on MRI reconstruction based on deep learning and Generative AI models which was featured and awarded in academic and industry conferences.
I co-founded Subtle Medical (StartX 2017), using deep learning technology to improve the efficiency and quality of medical imaging.
I co-founded Polarr (StartX 2014) and built new technologies (GPU rendering, edge-side DL, mobile computer vision) for photo retouching products and curation engine.
At Stanford, I am supervised by Professor John Pauly and Professor Greg Zaharchuk to apply deep learning and statistical methods on reconstruction to further push the limit of fast imaging and improving the acquisition, reconstruction and quantification of MRI. I am also leading projects on DL application in neuroimaging, PET/MRI, quantitative MRI etc.
At Tsinghua, my awarded undergraduate thesis work is focused on decoding human speech intention using neural signals. I have also interned at Qualcomm and Philips working on Machine Learning and Computational Imaging.
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