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Abstract. Multi-directional optical coherence tomography (MD-OCT) applies and extends the concept of angular compounding for speckle noise reduction to the area of OCT imaging. OCT images are acquired from a wide range of angles of view. Averaging of the rotated images therefore requires compensation of the parallax which is achieved by simple image registration for image reconstruction. Test measurements of a sample structure in a low and highly scattering environment show that the method improves the signal-to-noise ratio by a factor of 4 and hence reduces speckle noise significantly. Experimental results also show that the proposed averaging increases the performance of common edgedetection algorithms.

We introduce a simple model to produce EEG-like signals. The model is based on the assumption that the number of active nerve cells that generate an electric field, at a given time, is essentially chaotic. In accordance, we use the logistic equation together with a spike-like function to simulate the neuronal activity processes. With this model, we are able to generate EEG-like patterns, with quite a short time of calculation. Real pre-recorded neuronal and simulated signals, as well as their power spectra, are compared in terms of the main conventional EEG frequency peaks.

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