An Adaptive Super-Resolution Algorithm Applied to Magnetic Resonance Imaging
1Each year, many people are diagnosed with cancers such as brain cancers, worlwide. It is essential to have a short delay and high accuracy in diagnostic of fast spreading cancerous cells. Magnetic Resonance Imaging (MRI) is one of the important means in cancer diagnosis. In this context, various Super-Resolution (SR) methods have been proposed for the use in MRI scans after acquisition time. In this paper, an adaptive super-resolution algorithm is presented which can detect MRI scans defects and try to reconstruct them. As a consequence, the proposed SR algorithm may increase sensitivity and specificity of the output results. One of the important advantage of the proposed algorithm is its ability to maintain the specifications without any changs in significant part of the data. Thus, the proposed method can be emplyed in MRI for better results in real-time in terms of sensitivity and accuracy.