NEUROMAGNETOMETER COMPUTER SYSTEM

神经磁力计计算机系统

• 批准号: 3939811
• 负责人: R L MARTINO
• 金额: --
• 依托单位: CENTER FOR INFORMATION TECHNOLOGY
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/3939811
• 关键词: brain mapping; central neural pathway /tract; clinical biomedical equipment; computed axial tomography; computer assisted diagnosis; computer graphics /printing; computer system design /evaluation; electroencephalography; epilepsy; generalized seizures; human subject; magnetoencephalography; mathematical model; nervous system disorder diagnosis; noninvasive diagnosis; patient monitoring device

The Medical Neurology Branch of NINCDS, the Biomedical Engineering and Instrumentation Branch of DRS, and the Computer Systems Laboratory of DCRT are collaborating on a research project to noninvasively localize epileptic discharge sources within the human brain utilizing neuromagnetic recording in conjunction with conventional electroencephalogram (EEG) recording. Many patients with seizure disorders exhibit low-level cellular discharges between seizures, indicated by interictal spikes in their EEG and magnetoencephalogram (MEG) recordings. This project involves the development of computer techniques for automating and enhancing the procedure that is presently used by NINCDS neurologists for determining the intracranial locations of the sources of interictal spikes in patients with epilepsy. During the past year, MEG and EEG signals containing interictal spikes were collected from a number of patients. Work began on the development of algorithms to process these signals using a commercially available digital signal processing software package. contour maps of the magnetic field generated on the surface of the head by interictal spikes are used to locate the putative brain sources int he three-dimensional cranial space. A number of commercially available contouring packages that could be used to create these maps were evaluated. In the future, algorithms will be developed to process the MEG and EEG signals including methods for removing interference from ambient noise sources, detecting interictal spikes automatically, and classifying spikes into types based on spike morphology using correlation techniques. Three-dimensional displays of the outline of the patient's head integrated with anatomical data obtained from CT and MRI scans will also be developed so that epileptic sources can be represented relative to actual brain anatomy.

NINCDS医学神经病学分会，生物医学