since 05 February 2011 :
View(s): 299 (2 ULiège)
Download(s): 144 (0 ULiège)
print        
Kian Jafari

An Adaptive Super-Resolution Algorithm Applied to Magnetic Resonance Imaging

(Volume 85 - Année 2016 — Actes de colloques — Special edition)
Article
Open Access

Attached document(s)

original pdf file
Keywords : cancerous cells, magnetic resonance imaging, super resolution algorithm

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.

To cite this article

Kian Jafari, «An Adaptive Super-Resolution Algorithm Applied to Magnetic Resonance Imaging», Bulletin de la Société Royale des Sciences de Liège [En ligne], Volume 85 - Année 2016, Actes de colloques, Special edition, 181 - 186 URL : https://popups.ulg.ac.be/0037-9565/index.php?id=5270.

About: Kian Jafari

Electrical Engineering Department, Shahid Beheshti University, Teheran, Iran, k_jafari@sbu.ac.ir