{"record_key":"sat2nu","identifier":"sat2nu","external_key":"228","title":"Sat2NU","summary":null,"url":"https://inventions.techventures.columbia.edu/products/sat2nu","json_url":"https://inventions.techventures.columbia.edu/products/sat2nu.json","object_key":"products","description":"This technology offers a modular deep learning framework called Sat2Nu for generating nonfat-suppressed images from fat-suppressed MRI scans. It employs a U-Net architecture optimized to process both image types, allowing for accurate training even with limited datasets. Validation studies demonstrated low reconstruction error in the generated images compared to true nonfat-suppressed images, supporting its potential for improving MRI workflows without requiring additional scan acquisitions, particularly in breast imaging applications.","attributes":[],"related":[]}