Abstract
The quantitative analysis of MRI data is becoming increasingly important in the evaluation of therapies for the treatment of MS. This paper describes a processing environment for the automatic quantification of lesion load from large ensembles of MR volume data. The main components of this approach are stereotaxic transformation and multispectral classification, supported by pre- and postprocessing techniques to reduce noise and correct for intensity non-uniformities. The results of the automated approach are compared with those obtained by manual lesion delineation, showing a significant lesion volume correlation of 0.94.
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Zijdenbos, A., Evans, A., Riahi, F., Sled, J., Chui, J., Kollokian, V. (1996). Automatic quantification of multiple sclerosis lesion volume using stereotaxic space. In: Höhne, K.H., Kikinis, R. (eds) Visualization in Biomedical Computing. VBC 1996. Lecture Notes in Computer Science, vol 1131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0046984
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DOI: https://doi.org/10.1007/BFb0046984
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