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Abstract #1161

Super Resolution of MR Images with Deep Learning Based k-space Interpolation

Madiha Arshad1, Mahmood Qureshi1, Omair Inam1, and Hammad Omer1
1Medical Image Processing Research Group (MIPRG), Dept. of Elect. & Comp. Engineering, COMSATS University, Islamabad, Pakistan


Super resolution of MR images can be used to speed up MRI scan time. However, super resolution is a highly ill-posed problem as the low-resolution images lack high frequency spatial information. In this paper, we propose a hybrid dual domain cascaded U-Net to restore the high-resolution images. Firstly, the U-Net operating in k-space domain is used to interpolate the missing k-space data points and then the U-Net operating in image domain provides a refined high-resolution solution image. Experimental results show a successful reconstruction of high resolution images by using only central 6.25% and 25% k-space data.

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