A scalable method to improve gray matter segmentation at ultra high field MRI

Article, Preprint English OPEN
De Martino, Federico; Schneider, Marian; Marquardt, Ingo; Haast, Roy A. M.;
(2018)
  • Publisher: Public Library of Science
  • Journal: PLoS ONE,volume 13,issue 6 (issn: 1932-6203, eissn: 1932-6203)
  • Publisher copyright policies & self-archiving
  • Related identifiers: doi: 10.1101/245738, doi: 10.1371/journal.pone.0198335, pmc: PMC5991408
  • Subject: Applied Mathematics | Algorithms | Magnetic Resonance Imaging | Research Article | Diagnostic Medicine | Mathematics | Anatomy | Cardiovascular Anatomy | MULTIDIMENSIONAL TRANSFER-FUNCTIONS | 7 TESLA | Diagnostic Radiology | Mathematical and Statistical Techniques | Radiology and Imaging | FMRI | Simulation and Modeling | Physical Sciences | HUMAN PARIETAL CORTEX | MODEL | Data Acquisition | IMAGES | COMPOSITIONAL DATA | Mathematical Functions | Biology and Life Sciences | Computer and Information Sciences | Neuroscience | Research and Analysis Methods | Physiology | Blood Vessels | Medicine | Body Fluids | AUDITORY AREAS | Neuroimaging | Q | R | Nervous System | Imaging Techniques | Science | Cerebrospinal Fluid | Journal Article | VISUAL-CORTEX | DIGITAL BRAIN PHANTOM | Medicine and Health Sciences | Transfer Functions

High-resolution (functional) magnetic resonance imaging (MRI) at ultra high magnetic fields (7 Tesla and above) enables researchers to study how anatomical and functional properties change within the cortical ribbon, along surfaces and across cortical depths. These stud... View more