yuanhaogong / deep-mri-reconstruction

Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction: Implementation & Demo

Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction

Reconstruct MR images from its undersampled measurements using Deep Cascade of Convolutional Neural Networks. This repository contains the implementation of DC-CNN using Theano and Lasagne and the simple demo on toy dataset borrowed from <http://mridata.org>. Note that the library requires the dev version of Lasagne and Theano, as well as pygpu backend for using CUFFT Library.

Usage:

python main_2d.py --num_epoch 5 --batch_size 2

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If you used this code for your work, you must cite the following work:

Schlemper, J., Caballero, J., Hajnal, J. V., Price, A., & Rueckert, D. A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction. Information Processing in Medical Imaging (IPMI), 2017

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The paper is also available on arXiv: <https://arxiv.org/pdf/1703.00555.pdf>