Transfer learning in deep neural network-based receiver coil sensitivity map estimation.
Journal:
Magma (New York, N.Y.)
Published Date:
Mar 27, 2021
Abstract
INTRODUCTION: The success of parallel Magnetic Resonance Imaging algorithms like SENSitivity Encoding (SENSE) depends on an accurate estimation of the receiver coil sensitivity maps. Deep learning-based receiver coil sensitivity map estimation depends upon the size of training dataset and generalization capabilities of the trained neural network. When there is a mismatch between the training and testing datasets, retraining of the neural networks is required from a scratch which is costly and time consuming.