MRI brain image analysis is of great significance for brain disease diagnosis, progression assessment, and monitoring of neurological conditions. Segmentation is a crucial process to determine volume, boundaries and morphology of specific brain structures in medical imaging. Manual segmentation however is time-consuming, laborious, and subjective, which significantly amplifies the need for automated processes. Now VASCage researcher Nadja Gruber, Malik Galijasevic (Medical University of Innsbruck, Dept. of Neuroradiology) and co-authors present an efficient deep learning approach for the automated segmentation of brain tissue in the high-ranking journal „Artificial Intelligence in Medicine“. Read More
