Publications
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Multimodal Brain Atlases
Source: 1998;.
Author: Toga AW, Thompson PM.
Abstract:
Atlasing strategies to represent neuroanatomic and functional data, as well as increasingly powerful techniques to manipulate, query and detect patterns in the resulting image databases, will accelerate our understanding of brain function. The demand for comprehensive neuroanatomic templates and stereotaxic methods to integrate brain maps is continuing to increase in pace with the vast amount of high resolution data being produced by 3-dimensional medical imaging devices. Access to the resulting digital image archives, as well as archive-based computational tools, will be fundamental to many future brain imaging investigations. The complexity and density of brain image data obligates the design of a framework which allows scientific and clinical data collected at numerous research centers to be compared and integrated. In this chapter, we have described mathematical and computational strategies for constructing a variety of atlases of the human brain. The atlas systems compile multi-modality brain maps in a stereotaxic reference space making it easier to measure, correlate, and interpret multi-subject, multi-modality brain data. Because of their digital format, and the diversity of the image datasets they contain, population-based brain atlases offer significant advantages for detecting abnormality in the brain. They also provide a powerful reference framework for biomedical research and clinical imaging investigations, and a basis to integrate brain data from geographically disparate research centers, across imaging modalities and in large human populations.
Source: 1998;.
Author: Toga AW, Thompson PM.
Abstract:
Atlasing strategies to represent neuroanatomic and functional data, as well as increasingly powerful techniques to manipulate, query and detect patterns in the resulting image databases, will accelerate our understanding of brain function. The demand for comprehensive neuroanatomic templates and stereotaxic methods to integrate brain maps is continuing to increase in pace with the vast amount of high resolution data being produced by 3-dimensional medical imaging devices. Access to the resulting digital image archives, as well as archive-based computational tools, will be fundamental to many future brain imaging investigations. The complexity and density of brain image data obligates the design of a framework which allows scientific and clinical data collected at numerous research centers to be compared and integrated. In this chapter, we have described mathematical and computational strategies for constructing a variety of atlases of the human brain. The atlas systems compile multi-modality brain maps in a stereotaxic reference space making it easier to measure, correlate, and interpret multi-subject, multi-modality brain data. Because of their digital format, and the diversity of the image datasets they contain, population-based brain atlases offer significant advantages for detecting abnormality in the brain. They also provide a powerful reference framework for biomedical research and clinical imaging investigations, and a basis to integrate brain data from geographically disparate research centers, across imaging modalities and in large human populations.