Quantifying Small Changes in Brain Ventricular Volume Using Non-rigid Registration

Abstract

Non-rigid registration can automatically quantify small changes in volume of anatomical structures over time by means of segmentation propagation. Here we use a non-rigid registration algorithm based on optimising normalised mutual information to quantify small changes in brain ventricular volume in MR images of a group of five patients treated with growth hormone replacement therapy and a control group of six volunteers. The lateral ventricles are segmented from each subject image by registering the brainweb image [1] which has this structure delineated. The mean (standard deviation) volume change measurements are 1.09cc (0.73cc) for the patient group and 0.08cc (0.62cc) for the volunteer group, this difference is statistically significant at the 1% level. We validate our volume change measurements by comparing them to previously published results obtained by visual inspection of difference images, and demonstrate high rank correlation coefficient (ρ = 0.7, n=11).KeywordsGrowth HormoneVentricular VolumeNormalise Mutual InformationSegmentation PropagationSmall Volume ChangeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.