Abstract #0535

Comparison of Tissue Classification Models for Automatic Brain MR Segmentation

Delphine Ribes^1,2, Bndicte Mortamet¹, Meritxell Cuadra Bach³, Clifford R. Jack⁴, Reto Meuli⁵, Gunnar Krueger¹, Alexis Roche¹

¹Advanced Clinical Imaging Technology, Siemens Medical Solutions-CIBM, Lausanne, Switzerland; ²Radiology, UNIL, Lausanne, Switzerland; ³Signal Processing Laboratory (LTS5), EPFL, Lausanne, Switzerland; ⁴Mayo Clin, Rochester, MN USA; ⁵Centre Hospitalier Universitaire Vaudois & University of Lausanne, Lausanne, Switzerland

Normal aging and numerous diseases such as Alzheimers disease (AD), vascular dementia (VD) and other neurodegenerative diseases lead to brain tissue changes over time. In the interest of disease classification and diagnosis, it is highly desirable to have reliable and automatic tools to measure brain tissue volumes. In this study, we compare volumetric and GM probabilities differences extracted from standard T1-weighted images using SPM8, VBM8 and an in-house automatic tissue classification algorithm called VEMTC.