Mohammad amin - Faculty of Computer Science and Engineering,
negin sadat ghaderian - Faculty of Computer Science and Engineering,
kian jafari - Faculty of Electrical Engineering, Shahid Beheshti University,Tehran, Iran
mojtaba vahidi asl - Faculty of Computer Science and Engineering,

Thousands of people are diagnosed with cancer each year and one of the hardest treatment courses belongs to brain tumors. When faced with fast spreading cancerous cells, time and accuracy in diagnosis are of essence, and one of the key tools in cancer diagnosis is MR imaging.In order to simplify diagnosis and abnormality localization, various super resolution methods have been utilized on MRI Scans after acquisition time. In this study we have developed an intelligent super-resolution algorithm that automatically detects MRI scan flaws and reconstructs the scan, accordingly. The superiority of this method compared to many others deployed, namely the super-resolution TDI, is its ability to maintain the specifications without changing any significant part of the data, therefore presenting an ideal and natural result in real-time.

Super resolution TDI, MRI resolution