This work aims to contribute to the lack of computational methods for medical image analysis and diagnosis about the study of cerebrospinal fluid volumes. In the first part, we focus on the volume assessment of the fluid spaces, from whole body images, in a population consisting of healthy adults and hydrocephalus patients. To help segmentation, these images, obtained from a recent "tissue-specific" magnetic resonance imaging sequence, highlight cerebrospinal fluid unlike its neigh borhood structures. We propose automatic segmentation and separation methods of the different spaces, which allow efficient and reproducible quantification. We show that the ratio of the total subarachnoid space volume to the ventricular one is a proportionality constant for healthy adults, to support a stable intracranial pressure. However, this ratio decreases and varies significantly among patients suffering from hydrocephalus. This ratio provides a reliable physiological index to help in the diagnosis of hydrocephalus. The second part of this work is dedicated to the fluid volume distribution analysis within the superior cortical subarachnoid space. Anatomical complexity of this space induces that it remains poorly studied. We propose two complementary methods to visualize the fluid volume distribution, and which both produce two-dimensional images from the original ones. These images, called relief maps, are used to characterize respectively, the fluid volume distribution and the fluid network, to classify healthy adults and patients with hydrocephalus, and to perform patient monitoring before and after surgery
