METHOD OF DIAGNOSING PATHOLOGY OF PARANASAL SINUSES BY RECOGNISING IMAGES Russian patent published in 2016 - IPC A61B6/00 G06F7/02 

FIELD: medicine.

SUBSTANCE: invention relates to medicine, X-ray imaging, digital image processing techniques and statistical methods of image recognition, can be used for diagnosing pathologies of maxillary and frontal sinuses. On X-ray image separating an “area of interest” by contours of sinus (P) and same orbit (O), latter is used as a reference image (EO) for identification and estimation of degree of pathology P. Digitising image contours of sampling and quantisation amplitude intensity pixel brightness on basis of resolution of image source and capacity of computer. Constructing histograms - statistical portraits images of contours P and O with evaluation of their brightness densities M, dispersions D, mean-square deviations (MSD) σ, density factor K_pl (ratio of density M_p of analysed contour P to density M_o of contour of same O, expressed in units of gray scale). Identifying state P from value K_pl= M_p/M_o. For K_pl < 1±σ fixing norm, for K_pl> 1 +σ - pathology P. To increase resolution of diagnosis of condition P image of selected contours of similar P and O are presented as a result of digitisation of same-size matrices of brightness. Forming variation series (VR) with evaluation of span of every VR Δx = x_max-x_min. Determining ratio of extreme elements of series η= x_max/_min, in primary approach by estimating condition P: norm - for Δx≅0, η≅1; pathology- Δx≠0, η> 1. Further, nature of pathology P is assessed quantitatively with coefficient of variation of V (ratio of SKO σ_x to density M_x of corresponding histogram). Pairs of similar contours P and O having a multimodal histogram, segmented by decomposition of each corresponding contour of matrix of intensity values of brightness into L submatrices size n_l×n, where n_l= n/L, n×n - dimension of initial matrix of contour. Constructing L corresponding histograms and estimate their quantitative characteristics M_l, D_l, σ_l, V_l, where l is number of segment. By comparative analysis of histograms segments of contours O are selected as OE of such l-th segment, histogram of which is homogeneous with minimum dispersion D_ol→min and coefficient of variation of V_ol→min. Fixing parameters of its histogram, performing differential topological decomposition of overall K_pl of analysed P into L coefficients of density of segments, each of which is defined by ratio of density M_pl of histogram of l-th segment of loop P to density of histogram of segment of contour O M_ol, selected as OE: K_pll=M_pl/M_ol. Based on topologic series of values K_pl and V segments of contour P {K_pl1, K_pl2, …, K_plL}; {V₁, V₂, …, V_L} estimating state P by local interpretation of its content.

EFFECT: method provides quantitative assessment of content paranasal P, degree of pathology thereof, localisation accuracy and differential diagnostics, possibility of classifying analysed pathology.

1 cl, 17 dwg, 3 ex, 2 tbl