Doctors have been using magnetic resonance imaging (MRI) on the brain for quite some time now. While it is effective in producing clear images of the human brain, there’s always room for improvement. Using artificial intelligence (AI), researchers of the ICAI Group-Computational Intelligence and Image Analysis – of the University of Malaga (UMA) have designed a new method that improves the resolution of such brain scans.
Using a deep learning artificial neural network, the new model boosts the quality of the image’s resolution from low to high without any distortion at all. Karl Thurnhofer, researcher and main author of the study says that it’s because of this technique, identification can be done without the help of a human.
The study, published in the journal Neurocomputing, represents quite a big breakthrough for science as the new model is the most accurate and efficient we’ve ever seen. “So far, the acquisition of quality brain images has depended on the time the patient remained immobilized in the scanner; with our method, image processing is carried out later on the computer,” explains Thurnhofer. Specialists can now use the algorithm to find brain-related pathologies such as cancer, physical injuries, or language disorders with much greater accuracy than ever before.