ABSTRACT
Reference brains are indispensable tools in human brain mapping, enabling integration of multimodal data into an anatomically realistic standard space. Available reference brains, however, are restricted to the macroscopic scale and do not provide information on the functionally important microscopic dimension. We created an ultrahigh-resolution three-dimensional (3D) model of a human brain at nearly cellular resolution of 20 micrometers, based on the reconstruction of 7404 histological sections. "BigBrain" is a free, publicly available tool that provides considerable neuroanatomical insight into the human brain, thereby allowing the extraction of microscopic data for modeling and simulation. BigBrain enables testing of hypotheses on optimal path lengths between interconnected cortical regions or on spatial organization of genetic patterning, redefining the traditional neuroanatomy maps such as those of Brodmann and von Economo.
Subject(s)
Brain Mapping , Brain/anatomy & histology , Brain/cytology , Imaging, Three-Dimensional , Aged , Cerebral Cortex/anatomy & histology , Cerebral Cortex/cytology , Female , Humans , Image Processing, Computer-Assisted , Magnetic Resonance Imaging , MicrotomyABSTRACT
Intraoperative management of bleeding is a critical skill all surgeons must possess. It is, however, very challenging to create a safe and realistic learning environment for its acquisition. In this paper, we propose a simple and efficient approach to integrate blood circulation to computerized surgical simulation systems and allow for real-time processing of punctures, ruptures, and cauterization of blood vessels. Blood pressures and flows are calculated using a system of ordinary differential equations, which can be simulated very efficiently. The equation system itself is constructed using a graph of the vessels' connectivity extracted from magnetic resonance angiograms (MRA) and completed with virtual vessels deduced from the principle of minimum work. Real-time performances of the method are assessed and results are demonstrated on ten patients who underwent a MRA before removal of a brain tumor.
Subject(s)
Computer-Assisted Instruction/methods , Hemorrhage/physiopathology , Hemorrhage/surgery , Hemostasis, Surgical/education , Models, Cardiovascular , Blood Loss, Surgical/prevention & control , Blood Pressure , Blood Vessels/physiology , Blood Vessels/physiopathology , General Surgery/education , HumansABSTRACT
We present a novel approach to fluid simulation over complex dynamic geometry designed for the specific context of virtual surgery simulation. The method combines a surface-based fluid simulation model with a multi-layer depth peeling representation to allow realistic yet efficient simulation of bleeding on complex surfaces undergoing geometry and topology modifications. Our implementation allows for fast fluid propagation and accumulation over the entire scene, and runs on the GPU at a constant low cost that is independent of the amount of blood in the scene. The proposed bleeding simulation is integrated in a complete simulator for brain tumor resection, where trainees have to manage blood aspiration and tissue/vessel cauterization while they perform virtual surgery tasks.
Subject(s)
Brain Neoplasms/surgery , Computer-Assisted Instruction/methods , Neurosurgical Procedures/education , Neurosurgical Procedures/instrumentation , Surgery, Computer-Assisted , Algorithms , Body Fluids , Brain Neoplasms/pathology , Cautery , Computer Graphics , Computer Simulation , Hemorrhage , Humans , Image Processing, Computer-Assisted , User-Computer InterfaceABSTRACT
Size and scale issues present a complexity problem in visualizing detailed 3D models built from sensor data. A model of Leonardo da Vinci's Mona Lisa, with its thin pictorial layer, illustrates the need for intuitive real-time processing tools that are seamlessly integrated with a multiresolution visualization environment.
