Reconstruction of multicontrast MR images through deep learning
Medical Physics2019Vol. 47(3), pp. 983–997
Citations Over TimeTop 10% of 2019 papers
Abstract
The proposed X-net and Y-net effectively reconstructed full images from down-sampled images, outperforming the conventional parallel-imaging, compressed-sensing and U-net methods and providing more realistic images in combination with a GAN. The developed networks potentially enable us to accelerate multicontrast anatomical MR imaging in routine clinical studies including T1-and T2-weighted imaging.
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