An Approach for Statistical Data Extraction from Photo Images of Pathological Biopsy Objects

Abstract

Abstract-The task of statistical data extraction from photo images of biomedical objects is important in biomedical diagnostics. For example, the analysis of photographic images of aortic valve taken after surgical operation can be used for further medical research. In this case, it is important to define the percentile correlation between the pathological and the macroscopically unchanged tissue. In this work, authors implement different methods for extracting the statistical data from images. The experimental results show the efficiency of the selected methods.

An Approach for Fast Statistical Data Extraction from Biomedical Objects

“…On the images of [1] there is lack -glare on biopsy objects. This problem was solved in [1] only in part.…”

“…Thus, new objects were obtained to create a class for use in the method "k Nearest-Neighbours". In [1], the input data were photo images of biopsy object. On the images of [1] there is lack -glare on biopsy objects.…”

“…In [1], the input data were photo images of biopsy object. On the images of [1] there is lack -glare on biopsy objects. This problem was solved in [1] only in part.…”

“…In those studies, the modification of "k Nearest-Neighbours" method was proposed. The method "Template Matching" [12], [13] for our task is described in [1].…”

“…The present paper is continuation of research that is described in [1]. Calcific aortic valve disease (CAVD) is an abnormal process that affects aortic valve leaflets characterised by progressive calcium deposition in the middle layer of the valve.…”