Individualized Gaussian process-based prediction and detection of local and global gray matter abnormalities in elderly subjects

• Published in: NeuroImage (Orlando, Fla.) Vol. 97; pp. 333 - 348
• Main Authors: Ziegler, G., Ridgway, G.R., Dahnke, R., Gaser, C.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 15.08.2014; Elsevier; Elsevier Limited; Academic Press
• Subjects: Adolescent; Adult; Age; Aged; Aged, 80 and over; Aging; Algorithms; Anatomy, Cross-Sectional; Artificial Intelligence; Bayesian inference; Biological and medical sciences; Brain morphology; Brain research; Computer Simulation; Fundamental and applied biological sciences. Psychology; Gaussian processes; Grants; Gray Matter - abnormalities; Gray Matter - pathology; Humans; Image Processing, Computer-Assisted - methods; Lifespan brain aging; Magnetic Resonance Imaging - methods; Medical imaging; Medical research; Middle Aged; NMR; Normal Distribution; Nuclear magnetic resonance; Parameter estimation; Pharmaceutical industry; Single case analysis; Standard deviation; Studies; Vertebrates: nervous system and sense organs; Young Adult; Single case analysis; Lifespan brain aging; Bayesian inference; Brain morphology; Gaussian processes; Human; Senescence; Morphology; Central nervous system; Encephalon

Structural imaging based on MRI is an integral component of the clinical assessment of patients with potential dementia. We here propose an individualized Gaussian process-based inference scheme for clinical decision support in healthy and pathological aging elderly subjects using MRI. The approach...