W L Nowinski1, A Thirunavuukarasuu. 1. Biomedical Laboratory, Kent Ridge Digital Laboratories, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. wieslaw@krdl.org.sg
Abstract
OBJECTIVE: This paper introduces a method for localization analysis of functional images assisted by a brain atlas. The usefulness of the system developed, based on this method, is analyzed for human brain mapping and neuroradiology. MATERIALS AND METHODS: We use an enhanced and extended electronic Talairach-Tournoux brain atlas, containing segmented and labeled subcortical structures, Brodmann's areas, and gyri. The brain atlas serves as a tool for anatomy referencing, segmentation, labeling, registration, and providing 3D anatomical relationships. The process of localization analysis is decomposed into five steps: data loading, feature extraction, data normalization, identification and editing of loci, and getting labels and values. This analysis is supported by near real-time data-to-atlas warping based on the Talairach transformation. Metanalysis is enabled by merging the current and external lists of activation loci. RESULTS: We have designed, developed, tested, and deployed a commercial system for atlas-assisted localization analysis of functional images. This is the first system where an electronic version of the Talairach-Tournoux brain atlas is used interactively for analysis of functional images. This system runs on personal computers and provides functions for a rapid normalization of anatomical and functional volumetric data, data segmentation and labeling, readout of Talairach coordinates, and data display. It also is empowered with several unique features including: interactive warping facilitating fine tuning of the data-to-atlas fit, a backtracking mechanism to compensate for missing landmarks and enhancing the outcome of the overall process of data analysis, navigation on the triplanar formed by the data and the atlas, multiple-images-in-one display with atlas-anatomy-function blending, a fast locus-controlled generation of results, editing of loci, multiple label display, and saving and reading of loci. The system normalizes a single image in near real-time (0.7 s), so analysis of anatomical and functional datasets can be done on-the-fly regardless of the number of slices. The same task performed by the state-of-the-art non-linear registration methods may require up to several days. CONCLUSIONS: The system is a useful tool for atlas-assisted localization analysis and a helpful adjunct to function/location metanalysis in human brain mapping research. It is also a step forward in bringing the atlas and the clinical data together within a practical and powerful solution that is fast and flexible, yet low-cost and affordable.
OBJECTIVE: This paper introduces a method for localization analysis of functional images assisted by a brain atlas. The usefulness of the system developed, based on this method, is analyzed for human brain mapping and neuroradiology. MATERIALS AND METHODS: We use an enhanced and extended electronic Talairach-Tournoux brain atlas, containing segmented and labeled subcortical structures, Brodmann's areas, and gyri. The brain atlas serves as a tool for anatomy referencing, segmentation, labeling, registration, and providing 3D anatomical relationships. The process of localization analysis is decomposed into five steps: data loading, feature extraction, data normalization, identification and editing of loci, and getting labels and values. This analysis is supported by near real-time data-to-atlas warping based on the Talairach transformation. Metanalysis is enabled by merging the current and external lists of activation loci. RESULTS: We have designed, developed, tested, and deployed a commercial system for atlas-assisted localization analysis of functional images. This is the first system where an electronic version of the Talairach-Tournoux brain atlas is used interactively for analysis of functional images. This system runs on personal computers and provides functions for a rapid normalization of anatomical and functional volumetric data, data segmentation and labeling, readout of Talairach coordinates, and data display. It also is empowered with several unique features including: interactive warping facilitating fine tuning of the data-to-atlas fit, a backtracking mechanism to compensate for missing landmarks and enhancing the outcome of the overall process of data analysis, navigation on the triplanar formed by the data and the atlas, multiple-images-in-one display with atlas-anatomy-function blending, a fast locus-controlled generation of results, editing of loci, multiple label display, and saving and reading of loci. The system normalizes a single image in near real-time (0.7 s), so analysis of anatomical and functional datasets can be done on-the-fly regardless of the number of slices. The same task performed by the state-of-the-art non-linear registration methods may require up to several days. CONCLUSIONS: The system is a useful tool for atlas-assisted localization analysis and a helpful adjunct to function/location metanalysis in human brain mapping research. It is also a step forward in bringing the atlas and the clinical data together within a practical and powerful solution that is fast and flexible, yet low-cost and affordable.