The method for displacement correction along the slow axis of Optical Coherence Tomography (OCT) data volumes is presented. The method is based on the recursive replacement of the next displaced OCT measurements by the weighted summation of itself and the previous OCT measurement in the slow axis dimension already corrected for the displacement. The values of the appropriate weight multipliers were defined from the local correlation of the two measurements. The proposed method was used as a preprocessing step for Optical Coherence Angiography processing of the OCT data. Substantial reduction of the motion-induced stripe artifact was demonstrated.

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The method for displacement correction along the slow axis of Optical Coherence Tomography (OCT) data volumes is presented. The method is based on the recursive replacement of the next displaced OCT measurements by the weighted summation of itself and the previous OCT measurement in the slow axis dimension already corrected for the displacement. The values of the appropriate weight multipliers were defined from the local correlation of the two measurements. The proposed method was used as a preprocessing step for Optical Coherence Angiography processing of the OCT data. Substantial reduction of the motion-induced stripe artifact was demonstrated.

The problem of recognising single sparsely located scatterers against the noise background in the image obtained by the method of optical coherence tomography (OCT) is considered. An identification method based on the use of specific scanning features upon OCT image registration and on the statistical analysis of image fragments is proposed. The efficiency of the method is demonstrated experimentally in the diagnosis of otitis media with effusion. The approach can be used in the development of automated algorithms for determining the presence of highly transparent effusion in the middle ear cavity of a human with acute otitis media with effusion, including postoperative one.