Application of Tikhonov Regularization to Super-Resolution Reconstruction of Brain MRI Images

This paper presents an image super-resolution method that enhances spatial resolution of MRI images in the slice-select direction. The algorithm employs Tikhonov regularization, using a standard model of imaging process and reformulating the reconstruction as a regularized minimization task. Our experimental result shows improvements in both signal-to-noise ratio and visual quality.

• Type: Conference
• Year: 2007
• Where: MIMI
• Authors: Xin Zhang, Edmund Y. Lam, Ed X. Wu, Kenneth K. Y. Wong
• Keywords: Algorithm Employs Tikhonov, Image Super-resolution Method, Medical Imaging, MIMI 2007, Regularized Minimization Task