Summary
In this article we present our research into the subject of reducing the influence of noise on evaluation of perfusion parameters, such as CBF, CBV or MTT. Noise can be present on some pixels of study slices, therefore it can lead to artifacts in calculated concentration time curves and blur the final results.
To minimize influence from these factors we propose method that is different from commonly used. Generally noise reduction is done by filtering (smoothing, blurring), which is not always producing good results, as many information from image is lost. Therefore more effective is using the interpolation methods.
We have studied different interpolation techniques and compared them numerically. Tests have proven that using our method leads to better, more accurate estimation of perfusion parameters. It also seems that large window Sinc interpolation gives the best results.
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Kartaszyński, R.H., Mikołajczak, P. (2010). Noise Influance Reduction in Estimation of CBF, CBV and MTT, MRI Perfusion Parameters. In: Choraś, R.S. (eds) Image Processing and Communications Challenges 2. Advances in Intelligent and Soft Computing, vol 84. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16295-4_26
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DOI: https://doi.org/10.1007/978-3-642-16295-4_26
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