In the presented work, a method of reconstruction of structural images in endoscopic optical coherence tomography based on taking into account speckle patterns by using the operations of morphological erosion and expansion is considered. The proposed algorithm for reducing the level of speckle noise to improve the quality of visualization in endoscopic optical coherence tomography was practically implemented in the LabVIEW environment. Distinctive features of the proposed algorithm are morphological processing of B-scans, filtering by convolution before morphological processing of B-scans, and multilevel filtering of A-scans and B-scans consisting of them. A series of computer experiments showed a stable increase in the signal-to-noise ratio and contrast of the obtained structural images when using the developed algorithm. The proposed algorithm for reducing the level of speckle noise in structural images can be used in medical technologies to visualize the internal structure of cavities and body tracts.

Keywords: speckle noise, optical coherence tomography, endoscopic systems, structural image, morphological erosion, morphological dilation, speckle reduction, coherence probing depth

An algorithm for numerical simulation of optical structure disturbance of biomedical objects is described. The key features of the presented algorithm are: posterization of CT or MRI scans, subsequent encoding and manual identification of each biological tissue, assigning it tabular optical properties. The described algorithm can be used in diffuse optical tomography (DOT) for numerical simulation of optical properties of biomedical objects of their constituent with variable spatial resolution. Numerical simulation showed that the presented algorithm allows us to describe the optical structure of biological tissue with data validity >90%.

Keywords: optical properties of biological tissues, time-resolved diffuse optical tomography, forward problem, turbid media, posterization

Biological tissue optical structure disturbance localization algorithm for time-resolved diffuse optical tomography is described. The key features of the presented algorithm are: the initial approximation for the spatial distribution of the optical characteristics based on the Homogeneity Index (HI) and the assumption that all the absorbing and scattering inhomogeneities in an investigated object are spherical and have the same absorption and scattering coefficients. The described algorithm can be used in the brain structures diagnosis, in traumatology and mammography.

Keywords: time-resolved diffuse optical tomography, localization of optical inhomogeneities, forward problem, inverse problem, homogeneity index