Rmn cerebral8/11/2023 Warnking, J., Guérin-Dugué, A., Chéhikian, A., et al.: Retinotopical mapping of visual areas using fMRI and a fast cortical flattening algorithm. and Garbay, C.: A cooperative framework for segmentation of MRI brain scans. and Sereno, M.: Cortical surface-based analysis I: segmentation and surface reconstruction. Journal of Cognitive Neuroscience 8 (1996) 1–28.ĭale, A. H., et al.: Computerized mappings of the cerebral cortex: a multiresolution flattening method and a surface-based coordinate system. IEEE Trans Med Imag 16 (1997) 852–863.Ĭollins, D., Zijdenbos, A., Kollokian, V., et al.: Design and construction of a realistic digital brain phantom. A.: Creating connected representations of cortical gray matter for functional MRI visualization. Journal of Cognitive Neuroscience 12 (2001) 739–752. T.: Visualization and measurement of the cortical surface. J., Bandettini, P., et al.: Mapping striate and extrastriate visual areas in human cerebral cortex. A.: Computational neuroimaging of human visual cortex. et al.: Functional and structural mapping of human cerebral cortex: solutions are in the surfaces. D., et al.: From retinotopy to recognition: fMRI in human visual cortex. and Shipp, S.: The functional logic of cortical connections. We report in detail our multi-agent approach and results obtained on MRI brain scans. Incremental refinement of the segmentation is obtained through the combination, distribution and opposition of solutions concurrently proposed by the agents, via respectively three types of cooperation: integrative, augmentative and confrontational. Constraints that drive the agents behavior, based on topographic relationships and radiometric information, are gradually gained and refined during the segmentation progress. Qualitative maps are used as a common framework to represent knowledge. segmentation of one type of tissue, is dynamically adapted with respect to their position in the image. To extract domain and control knowledge from the image, we propose to use situated cooperative agents whose dedicated behavior, i.e. To cope with the difficulty of MRI brain scans automatic segmentation, we need to constrain and control the selection and the adjustment of processing tools depending on the local image characteristics.
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