Back to search

Article

CS-MRI Reconstruction Using an Improved GAN with Dilated-Residual Networks and Channel Attention Mechanism

2023-07-11

Abstract excerpt

Compressed Sensing (CS) MRI has shown great potential in enhancing time efficiency. Deep learning techniques, specifically Generative Adversarial Networks (GANs), have emerged as potent tools for speedy CS-MRI reconstruction. Yet, as the complexity of deep learning recon-struction models increases, this can lead to prolonged reconstruction time and challenges in achieving convergence. In this study we present a no...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
97909f5a-921a-5e6c-a7cb-465177b22e50
DOI
10.20944/preprints202307.0666.v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
CS-MRI Reconstruction Using an Improved GAN with Dilated-Residual Networks and Channel Attention MechanismDOI 10.20944/preprints202307.0666.v1
Select a neighboring publication to make it the new centre.