An evolutionary neural architecture search for magnetic resonance image reconstructions

Samira Vafay Eslahi1,2, Jian Tao3,4, Jim Ji5,6

  • 1Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA. vafayeslahisamira@gmail.com.

Summary

Automated design of convolutional neural networks (CNNs) using genetic algorithms (GAs) significantly enhances magnetic resonance imaging (MRI) reconstruction accuracy. This approach eliminates manual tuning, offering an efficient solution for medical imaging deep learning models.