Abstract
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.
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Capozza, M., Iannetti, G.D., Marx, J., Cruccu, G., Accornero, N. (2002). An Artificial Neural Network for 3D Localization of Brainstem Functional Lesions. In: Colosimo, A., Sirabella, P., Giuliani, A. (eds) Medical Data Analysis. ISMDA 2002. Lecture Notes in Computer Science, vol 2526. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36104-9_21
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DOI: https://doi.org/10.1007/3-540-36104-9_21
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