The human brainstem is a highly complex structure where even small lesions can give rise to a variety of symptoms and signs. Localizing the area of dysfunction within the brainstem is often a difficult task. To make localization easier, we have developed a neural net system, which uses 72 clinical and neurophysiological data inputs and displays it (using 5268 voxels) on a three-dimensional model of the human brainstem. The net was trained by means of a back-propagation algorithm, over a pool of 580 example-cases. Assessed on 200 test-cases, the net correctly localized 83.6% of the target voxels; furthermore the net correctly localized the lesion in 31/37 patients. Because our computer-assisted method provides a reliable and quantitative localization of brainstem areas of dysfunction and can be used as a 3D interactive functional atlas, we expect that it will prove useful as a diagnostic tool for assessing focal brainstem lesions.
CITATION STYLE
Capozza, M., Iannetti, G. D., Marx, J. J., Cruccu, G., & Accornero, N. (2002). An artificial neural network for 3D localization of brainstem functional lesions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2526, pp. 186–197). Springer Verlag. https://doi.org/10.1007/3-540-36104-9_21
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