Estimation of CSF, white and gray matter volumes in hydrocephalic children using fuzzy clustering of MR images.

An algorithm and set of procedures for measuring volumes of cerebrospinal fluid (CSF), white matter, and gray matter from transaxial magnetic resonance images (MRI) of the brain are described. The algorithm is a variant of the fuzzy c-means clustering method for texture identification. This technique is used mainly to solve the problem of volume averaging of tissue compartments, but also has other advantages. It is fast, accurate, and relatively operator independent. Furthermore, it does not depend on statistical assumptions such as data normality, nor does it require any a priori heuristics. The procedure was tested successfully on imaged phantoms of known volume composition and compared with results achieved using a standard morphometric measurement approach. The procedure was also applied to brain MRIs of three clinically normal children and three age-matched children with hydrocephalus using both proton density and T2-weighted images. The algorithm was able to detect the expected increased amounts of CSF and decreased amounts of white matter characteristic of the hydrocephalic brain.