One Model to Synthesize Them All: Multi-contrast Multi-scale Transformer for Missing Data Imputation

no code implementations • 28 Apr 2022 • Jiang Liu, Srivathsa Pasumarthi, Ben Duffy, Enhao Gong, Keshav Datta, Greg Zaharchuk

In this work, we formulate missing data imputation as a sequence-to-sequence learning problem and propose a multi-contrast multi-scale Transformer (MMT), which can take any subset of input contrasts and synthesize those that are missing.

Image Generation Imputation