## 1 Introduction  
Medical imaging is widely used for visualizing the interior of the body non-invasively for clinical diagnosis [1; 2; 3; 4]. The two most common imaging techniques are computed tomography (CT) and magnetic resonance imaging (MRI). CT uses ionizing radiation and measures the radiation attenuation which is proportional to the image intensity. Dense structures, such as bones, have high attenuation thus high intensity. Soft structures, such as the brain, have low attenuation and thus low intensity. MRI uses radio frequencies to resonate hydrogen atoms, and detects the difference of signal recovery under influence of designed pulse sequence. It shows contrast between soft tissues. The MR imaging protocol can be customized to adjust image intensity based on desired features, such as flow phenomenon. Both imaging techniques output gray scale intensity maps for distinguishing diseased and normal tissue. In addition to clinical diagnosis, medical images are also used for constructing meshes for computational modeling in simulation studies, including hemodynamic studies [5; 6; 7; 8], traumatic brain injury [9; 10; 11], and cerebrospinal fluid flow studies [12; 13; 14; 15; 16; 17; 18]. Simulations with anatomical meshes and computational modeling provide results for experiments that are not easily performed, such as _in vivo_ human experiments. It also provides results within a short amount of time compared to hands on experiments. There also exists mesh-free techniques for simulation [19]. Anatomical meshes are a necessary source for surgical planning with haptics control in virtual reality [20; 21; 22; 23]. By assigning different physical properties to individual mesh structures, one can emulate the impact upon contact to better understand the spatial and physical relationships of the anatomical structures. This allows surgeons to simulate and practice surgeries to better assess and adjust the procedures to reduce the risks involved in invasive surgery. The meshes also allow better visualization of the anatomy using cutting edge immersive 3D displays [21; 22; 24]. Current visualization of medical images are confined to 2D display, which shows the image slices sequentially. Segmentation algorithms are used to extract certain features for surface and volumetric rendering. However, the interaction and display is still presented in a planar screen. By combining volume rendering of original medical images with displaying volumetric meshes in an immersive environment, one can explore and interact with the anatomical structures in a global sense to better understand and diagnose the diseased situation, such as intracranial stenosis. Nevertheless, finite resolution of the medical images lead to uncertainty in identifying the structures for mesh construction. Intensity threshold algorithms may encounter difficulties in identifying voxelsaround interfaces between structures especially in imaging studies of the brain. Several groups use manual input on top of image processing to better identify the interfaces. [PERSON] proposed Delaunay-based technique for generating watertight surface and volume meshes [25]. The Cerefy atlas [26; 27; 28] exhibits a detailed whole brain segmentation for one subject using various image processing algorithms with manual modification. [PERSON] [29] uses image processing with manual modification to reconstruct the cerebrospinal fluid (CSF) space. Manual segmentation requires anatomical knowledge with extensive man hours (>20 h) and is highly operator dependent. To date, there exists no fully automatic image segmentation for the whole brain. In this paper, we propose an automatic image processing pipeline that takes multiple MRI studies and generates computational meshes for major compartments of the brain, composed of grey and white matter, cerebrospinal fluid space, skull and scalp, and arteries and veins. We first describe the imaging protocols that were used to acquire the images. Then, discuss various image processing algorithms that were used to segment the different structures.