University of Minnesota

Seyed Amir Hossein Hosseini

Mehmet Akcakaya

Burhaneddin Yaman

Self-supervised training of machine learning ('ML') algorithms for reconstruction in inverse problems are described. These techniques do not require fully sampled training data. As an example, a physics-based ML reconstruction can be trained without requiring fully-sampled training data. In this way, such ML-based reconstruction algorithms can be trained on existing databases of undersampled images or in a scan-specific manner.

Growing community of inventors

Minneapolis, MN, United States of America

Seyed Amir Hossein Hosseini